Percorso formativo

Educational objectives

General objectives
The course combines practical sessions and exercises to introduce the main data analysis techniques (including supervised and unsupervised learning techniques) and operational tools (including R, Excel and generative AI) available for developing data analyses to support 'business activities'. Each technique presented will be accompanied by at least one case study, presented through interactive lab sessions.
More precisely, the general objectives of the course are:
• Present an overview of the role of the Data Analyst and the objectives of the possible analyses to be implemented (business purpose).
• To introduce the main software available for the implementation of the analysis techniques presented during the course.
• Present the operational use of generative AI tools for data analysis.
• Present the basic techniques for data mining and scraping and text analysis.
• Present the implementation of estimation, time series and clustering techniques.
• Provide laboratory sessions for the practical implementation of the techniques presented during the course.
• Present various applications in the field of economics and management as potential group work, to be developed by students according to their personal interests and backgrounds.
• Provide the rudiments of data presentation and data storytelling with advanced operational tools (such as shiny or powerBI-based platforms).
• To interact with students through assisted workshops, oral presentations and the realization of a project on real data.

Specific objectives
• Knowledge and understanding: demonstrate knowledge of developing data analysis techniques;
• Apply knowledge and understanding: apply specific software tools to develop data analysis techniques;
• Critical and judgment skills: be able to evaluate data sources to be used critically and independently, subsequently choosing the appropriate analysis method and implementing it correctly;
• Communication skills: be able to communicate analysis results and related information to different types of interlocutors;
• Learning ability: develop the skills necessary to independently apply and develop the various techniques learned during the course.

Educational objectives

The course aims to provide the fundamental principles of finance, to
present basilar techniques and models that are required for the
valuation of financial instruments, the analysis of investment
strategies and the management of risks.
Risultati di apprendimento attesi (Inglese):
The course should provide the
students with the in-depth knowledge of key concepts and topics that
every finance professional should be familiar with. In particular, it
should allow to address the problems of valuation and risk management of
the most commonly traded financial instruments.

Educational objectives

ENG
GENERAL OBJECTIVES
The course aims to provide students with a fundamental understanding of concepts and tools relevant to marketing. Specifically, the course aims to help students understand: the main forces of the marketing environment; the marketing information system; consumer and business buying behaviors; the stages and tools for formulating and implementing a marketing strategy. Furthermore, through the analysis of a series of case studies, the course aims to develop students' critical analysis skills, enabling them to interpret and explain business behavior and outcomes within marketing strategies in light of the concepts learned during the course.

SPECIFIC OBJECTIVES
KNOWLEDGE AND UNDERSTANDING. The course will enable students to acquire knowledge and understanding of the main concepts and fundamental tools of Marketing. Students will learn to recognize and master best practices and success factors of Marketing and apply them in real-world contexts.

APPLICATIVE SKILLS. Thanks to the course, students will be able to formulate a marketing plan, as well as critically evaluate marketing strategies.

JUDGMENT AUTONOMY. The course will empower students to choose, given the main environmental forces, the characteristics of the enterprise and innovation, the best marketing strategies. Additionally, students will develop the ability to critically analyze marketing.

COMMUNICATION SKILLS. By the end of the course, students will be able to explain marketing concepts using internationally established terminology and models, organize information and data in a format and reporting process understandable to professionals.

LEARNING ABILITY. Students will develop independent study skills and critical understanding and evaluation of marketing strategies and related tools.

Educational objectives

The course provides students the tools to understand and manage the main
issues relating to corporate finance, investment decision and business
finance. The course is aimed to explain and develop the main methods of
evaluating an investment project and issues related to sources of
financing and optimal financial structure.Risultati di apprendimento attesi (Inglese):
At the end of the course the
student will be able to: a) know the main financial sources, b)
determine the optimal financial structure, c) calculate the cost of
capital, d) select the best project among different alternatives, e)
assess the value of a company using the most common valuation methods.

Educational objectives

OBJECTIVES
The course aims to provide the basic knowledge of Quality in process management for organizations, through the definition and historical evolution of the concept (from Quality Control to Total Quality Management), the regulatory framework, methodologies for analysis and improvement. In particular, the course presents an applicative focus on process mapping and management and on Lean Six Sigma.

EXPECTED LEARNING OUTCOMES
Knowledge and understanding: in-depth knowledge of terminology and reference concepts for quality management, knowledge of the principles of Lean Manufacturing and knowledge of the Lean Six Sigma methodology. Capability: ability to develop analysis and mapping of processes for value generation and identification of waste from a Lean perspective, ability to set up and develop a project according to the requirements of the Lean Six Sigma methodology, through the application of all phases of DMAIC, identifying appropriate performance measurement tools and defining objectives and improvement programs.

Educational objectives

The course aims to introduce students to the reasons economic government intervention in the economy and the relevance of the presence of the public sector in economics advanced, offering the main models and institutional knowledge of the European and national level.
The course aims to make the student capable of reading and interpret the evolution of the public sector in our country and his major structural reform in the coming years, well also in order to seize the potential opportunities.

Educational objectives

To know the different theoretical approach of human resources management
policy / tools and application to specific case history. To be aware of
different processes such as Recruiting, Training, Performance
Appraisal, Potential and Competence Evaluation, People development,
Internal Communication. To be able to establish significant relations
between human resources methods / tools and industry vertical segments,
different business environments, organizational processes and companies
strategies.
Risultati di apprendimento attesi (Inglese):To be able to analyse
organizational phenomenon focusing human resources aspects in different
business contests. To be able to define different alternatives of HR
processes depending on business goals.

Educational objectives

OBJECTIVES. The course aims to provide the knowledge bases of the Smart Factories in the context of Industry 4.0 which is characterized as the Fourth Industrial Revolution through the analysis of the economic and technological scenario, the identification and classification of intervention key areas, the processes for a strategy 4.0 implementation, the definition of organizational models, the identification of design and management issues.
EXPECTED LEARNING OUTCOMES. Knowledge and understanding: Knowledge of the structural and operating characteristics of Smart Factories within the framework of Industry 4.0. Applying knowledge and understanding: Ability to develop analysis, model problems and identify best techniques for implementing Smart Production in a Smart Factory. The course requires preparation of a technical report (usually prepared in small working groups self-managed by students); the course also aims to promote the development of skills to apply the knowledge acquired through independent learning and teamworking, making independent judgment and communication skills.

Educational objectives

GENERAL OBJECTIVES
The course aims to provide students with a basic understanding of concepts and tools relevant to Innovation Management. Specifically, the course aims to help students understand: the forms, models, and sources of innovation; standard conflicts and the definition of dominant design; market entry timing choices; innovation protection mechanisms; the process of developing a new product; the integration of environmental sustainability into marketing strategy and new product development. Furthermore, through the analysis of a series of case studies, the course aims to develop students' critical analysis skills, enabling them to interpret and explain business behavior and outcomes within the context of technological innovation strategies in light of the concepts learned during the course.

SPECIFIC OBJECTIVES
KNOWLEDGE AND UNDERSTANDING. The course will enable students to acquire knowledge and understanding of the main concepts and fundamental tools of Innovation Management. Students will learn to recognize and master best practices and success factors of Innovation Management and apply them in real-world contexts.

APPLICATIVE SKILLS. Thanks to the course, students will be able to critically evaluate an enterprise's technological innovation strategies, as well as classify products based on their environmental impact.

JUDGMENT AUTONOMY. The course will empower students to choose, given the main environmental forces, the characteristics of the enterprise and innovation, the best technological innovation strategies. Additionally, students will develop the ability to critically analyze innovation management.

COMMUNICATION SKILLS. By the end of the course, students will be able to illustrate concepts of innovation management using internationally established terminology and models, organize information and data in a format and reporting process understandable to professionals.

LEARNING ABILITY. Students will develop independent study skills and critical understanding and evaluation of marketing and technological innovation strategies and related tools

Educational objectives

Gain cognitive and technical tools for statistical process control.Acquire methodologies of design of experiments for process improvementGain tools for acceptance sampling of a lotRisultati di apprendimento attesi (Inglese):Student must be able to:- plan and execute a statistical process control by control charts- plan a experiments campaign in order to achieve a technological model of a process- design a lot acceptance control

Educational objectives

This course aims providing knowledges and abilities in the field of Additive Manufacturing with regards to:

- Knowledge about several technologies by means of physical and chemical processes;

- Knowledge about design methods applied to the virtual model and its reparing;

- Ability to manage different processes choosing suitable parameters and fabrication strategies;

- Ability to plan, before the AM fabrication, post processing operation in order to comply with the design requirements;

- Ability to compare additive and traditional processes in order to choose the better one for a specific case;

- Ability to apply the acquired knowledges to case studies;

- Ability to provide a technological transfer.

Educational objectives

The course aims to describe the founding principles, the scope and the fundamental toolsand
methodologies of project management and of organizational processes.
Starting from the concept of integrated management of projects, all the
main methods for managing the performance variables of quality, time and
cost will be proposed. In line with the main standard processes of
project management the internationally standardized project management
terminology will be used. The course also intends to present the
principles and techniques of business process re-engineering and
management.Risultati di apprendimento attesi (Inglese):At the
end of the course the student will be able to plan a project starting
from the objectives of quality, time and cost defined by internal or
external customers of a company. She/he will also be able to critically
analyze an ongoing project proposing both organizational and managerial
improvements and both the use of correct project management
methodologies.

Educational objectives

The specific aim is to allow the student to use and expand the bulk of knowledge acquired during the course of study performing some activities in an industrial setting, a company, or a research laboratory.

Educational objectives

The course gives on-field experience of Operations Management, from an operational and technical point of view. The course develops one of the main topics of Operations Management, e.g. company-market relations, supply chain management, production and inventory management.

EXPECTED LEARNING OUTCOMES. Knowledge and understanding: Deepening and consolidation of the knowledge provided in the Operations Management course. Capability: Expected learning outcomes include the ability to develop analyses, model problems, and identify the best techniques for solving major characteristic problems in production management, materials management, logistics management, and supply chain management through project work and on-field experience.

Educational objectives

Main course’s objective is
developing digital competences to make citizens able to use Information
and Communication Technologies (ICT) at work, in day-to-day relationships, in
dealing with public services as well as in culture, entertainment, leisure and
when participating in community and political dialogues. This course contributes
to actualize the EU i2010 program “increasing social
inclusion through reducing digital divide to build a society for
all”. The course promotes ICT use also to put in action the Italian Digital
Administration Low as well as the ICT right use (art.3) and the Public
Administration Data Availability (art 50 capo V).

Educational objectives

The objective is to provide the management engineer with the basis for understanding the theory and principles of innovative optical, photothermal, photoacoustic, radiometric and thermographic techniques and instruments, and to understand the main applications together with their industrial relapses and with a deep analysis of the economical impacts and parameters.

The topics are organized to provide scientific technical expertise in order to work in the field of applied research, making easier the employment of the new engineer in industry.

Contents of the proposed course:

The course will provide the theoretical bases of the optical systems, the laser with its applications. Photothermal, photoacoustic, radiometric, and infrared techniques will be introduced for nonsdestructive evaluation and testing of materials, together with the many applications in different fields: industry, environment, energy, but also biology, medicine, and in the emerging sector of agri-food. Final comparisons will be introduced among the diagnostic techniques by using parameters of the management engeneering. The course contains also some experimental activities in laboratory and the data analysis and processing.

Educational objectives

The course aims at deepening the design, the implementation, the execution and the analysis of the results of
discrete event simulation models. Particular focus will be on the use of specialized software packages and languages
for discrete event simulation and their possible use in connection with optimization software. Students will be
directly involved in laboratory activities and in particular in the implementation of real case studies.

Knowledge and understanding:
Techniques for implementing a discrete event simulation model. Use of software packages dedicated to
discrete event simulation and their possible integration with optimization software.

Applying knowledge and understanding:
To be able to carry out a complete study of a real problem through discrete event simulation, from the preliminary analysis
of the processes, the implementation, up to the interpretation of the results.

Making judgements:
Knowing how to identify the fundamental characteristics of a real process for the construction of a model of
discrete event simulation. Knowing how to evaluate the impact of the output of a simulation on the real case in analysis.

Communication skills:
The laboratory activities will allow the student to learn communicating and sharing simulation models and their outputs.

Learning skills:
The laboratory activities will stimulate the students to the autonomous realization of simulation models, to teamwork,
and to the concrete application of the techniques learned in the course.

Educational objectives

The specific goal of these activities is to enable the students to merge their academic knowledge with professional skills.

Educational objectives

Gain cognitive and technical tools for statistical process control.Acquire methodologies of design of experiments for process improvementGain tools for acceptance sampling of a lotRisultati di apprendimento attesi (Inglese):Student must be able to:- plan and execute a statistical process control by control charts- plan a experiments campaign in order to achieve a technological model of a process- design a lot acceptance control

Educational objectives

This course aims providing knowledges and abilities in the field of Additive Manufacturing with regards to:

- Knowledge about several technologies by means of physical and chemical processes;

- Knowledge about design methods applied to the virtual model and its reparing;

- Ability to manage different processes choosing suitable parameters and fabrication strategies;

- Ability to plan, before the AM fabrication, post processing operation in order to comply with the design requirements;

- Ability to compare additive and traditional processes in order to choose the better one for a specific case;

- Ability to apply the acquired knowledges to case studies;

- Ability to provide a technological transfer.

Educational objectives

The course aims to describe the founding principles, the scope and the fundamental toolsand
methodologies of project management and of organizational processes.
Starting from the concept of integrated management of projects, all the
main methods for managing the performance variables of quality, time and
cost will be proposed. In line with the main standard processes of
project management the internationally standardized project management
terminology will be used. The course also intends to present the
principles and techniques of business process re-engineering and
management.Risultati di apprendimento attesi (Inglese):At the
end of the course the student will be able to plan a project starting
from the objectives of quality, time and cost defined by internal or
external customers of a company. She/he will also be able to critically
analyze an ongoing project proposing both organizational and managerial
improvements and both the use of correct project management
methodologies.

Educational objectives

The specific aim is to allow the student to use and expand the bulk of knowledge acquired during the course of study performing some activities in an industrial setting, a company, or a research laboratory.

Educational objectives

The course gives on-field experience of Operations Management, from an operational and technical point of view. The course develops one of the main topics of Operations Management, e.g. company-market relations, supply chain management, production and inventory management.

EXPECTED LEARNING OUTCOMES. Knowledge and understanding: Deepening and consolidation of the knowledge provided in the Operations Management course. Capability: Expected learning outcomes include the ability to develop analyses, model problems, and identify the best techniques for solving major characteristic problems in production management, materials management, logistics management, and supply chain management through project work and on-field experience.

Educational objectives

Main course’s objective is
developing digital competences to make citizens able to use Information
and Communication Technologies (ICT) at work, in day-to-day relationships, in
dealing with public services as well as in culture, entertainment, leisure and
when participating in community and political dialogues. This course contributes
to actualize the EU i2010 program “increasing social
inclusion through reducing digital divide to build a society for
all”. The course promotes ICT use also to put in action the Italian Digital
Administration Low as well as the ICT right use (art.3) and the Public
Administration Data Availability (art 50 capo V).

Educational objectives

The objective is to provide the management engineer with the basis for understanding the theory and principles of innovative optical, photothermal, photoacoustic, radiometric and thermographic techniques and instruments, and to understand the main applications together with their industrial relapses and with a deep analysis of the economical impacts and parameters.

The topics are organized to provide scientific technical expertise in order to work in the field of applied research, making easier the employment of the new engineer in industry.

Contents of the proposed course:

The course will provide the theoretical bases of the optical systems, the laser with its applications. Photothermal, photoacoustic, radiometric, and infrared techniques will be introduced for nonsdestructive evaluation and testing of materials, together with the many applications in different fields: industry, environment, energy, but also biology, medicine, and in the emerging sector of agri-food. Final comparisons will be introduced among the diagnostic techniques by using parameters of the management engeneering. The course contains also some experimental activities in laboratory and the data analysis and processing.

Educational objectives

The course aims at deepening the design, the implementation, the execution and the analysis of the results of
discrete event simulation models. Particular focus will be on the use of specialized software packages and languages
for discrete event simulation and their possible use in connection with optimization software. Students will be
directly involved in laboratory activities and in particular in the implementation of real case studies.

Knowledge and understanding:
Techniques for implementing a discrete event simulation model. Use of software packages dedicated to
discrete event simulation and their possible integration with optimization software.

Applying knowledge and understanding:
To be able to carry out a complete study of a real problem through discrete event simulation, from the preliminary analysis
of the processes, the implementation, up to the interpretation of the results.

Making judgements:
Knowing how to identify the fundamental characteristics of a real process for the construction of a model of
discrete event simulation. Knowing how to evaluate the impact of the output of a simulation on the real case in analysis.

Communication skills:
The laboratory activities will allow the student to learn communicating and sharing simulation models and their outputs.

Learning skills:
The laboratory activities will stimulate the students to the autonomous realization of simulation models, to teamwork,
and to the concrete application of the techniques learned in the course.

Educational objectives

The specific goal of these activities is to enable the students to merge their academic knowledge with professional skills.

Educational objectives

General objectives
The course combines practical sessions and exercises to introduce the main data analysis techniques (including supervised and unsupervised learning techniques) and operational tools (including R, Excel and generative AI) available for developing data analyses to support 'business activities'. Each technique presented will be accompanied by at least one case study, presented through interactive lab sessions.
More precisely, the general objectives of the course are:
• Present an overview of the role of the Data Analyst and the objectives of the possible analyses to be implemented (business purpose).
• To introduce the main software available for the implementation of the analysis techniques presented during the course.
• Present the operational use of generative AI tools for data analysis.
• Present the basic techniques for data mining and scraping and text analysis.
• Present the implementation of estimation, time series and clustering techniques.
• Provide laboratory sessions for the practical implementation of the techniques presented during the course.
• Present various applications in the field of economics and management as potential group work, to be developed by students according to their personal interests and backgrounds.
• Provide the rudiments of data presentation and data storytelling with advanced operational tools (such as shiny or powerBI-based platforms).
• To interact with students through assisted workshops, oral presentations and the realization of a project on real data.

Specific objectives
• Knowledge and understanding: demonstrate knowledge of developing data analysis techniques;
• Apply knowledge and understanding: apply specific software tools to develop data analysis techniques;
• Critical and judgment skills: be able to evaluate data sources to be used critically and independently, subsequently choosing the appropriate analysis method and implementing it correctly;
• Communication skills: be able to communicate analysis results and related information to different types of interlocutors;
• Learning ability: develop the skills necessary to independently apply and develop the various techniques learned during the course.

Educational objectives

- To address the methodological principles underlying many phases of the life cycle of information systems, with reference not only to technological aspects, but also and above all to those that require attention to the organizational and economic context
- Enrich students' cultural heritage through a series of monographic or seminar contributions

Educational objectives

ENG
GENERAL OBJECTIVES
The course aims to provide students with a fundamental understanding of concepts and tools relevant to marketing. Specifically, the course aims to help students understand: the main forces of the marketing environment; the marketing information system; consumer and business buying behaviors; the stages and tools for formulating and implementing a marketing strategy. Furthermore, through the analysis of a series of case studies, the course aims to develop students' critical analysis skills, enabling them to interpret and explain business behavior and outcomes within marketing strategies in light of the concepts learned during the course.

SPECIFIC OBJECTIVES
KNOWLEDGE AND UNDERSTANDING. The course will enable students to acquire knowledge and understanding of the main concepts and fundamental tools of Marketing. Students will learn to recognize and master best practices and success factors of Marketing and apply them in real-world contexts.

APPLICATIVE SKILLS. Thanks to the course, students will be able to formulate a marketing plan, as well as critically evaluate marketing strategies.

JUDGMENT AUTONOMY. The course will empower students to choose, given the main environmental forces, the characteristics of the enterprise and innovation, the best marketing strategies. Additionally, students will develop the ability to critically analyze marketing.

COMMUNICATION SKILLS. By the end of the course, students will be able to explain marketing concepts using internationally established terminology and models, organize information and data in a format and reporting process understandable to professionals.

LEARNING ABILITY. Students will develop independent study skills and critical understanding and evaluation of marketing strategies and related tools.

Educational objectives

The course provides students the tools to understand and manage the main
issues relating to corporate finance, investment decision and business
finance. The course is aimed to explain and develop the main methods of
evaluating an investment project and issues related to sources of
financing and optimal financial structure.Risultati di apprendimento attesi (Inglese):
At the end of the course the
student will be able to: a) know the main financial sources, b)
determine the optimal financial structure, c) calculate the cost of
capital, d) select the best project among different alternatives, e)
assess the value of a company using the most common valuation methods.

Educational objectives

The course is designed to provide students the methodologies to apply to management control systems. The focus is on management and criteria for judging strategies and actions. The conceptual framework for the course is Balanced Scorecard. The course is designed to allow students to gain knowledge related to how managers design, implement and use Balanced Scorecard(BSC).Risultati di apprendimento attesi (Inglese):
After completing this course student will be able to:a) understand management control systemsb) solve control design problemsc) analyze and discuss BSC design

Educational objectives

This course aims at addressing important strategic aspects and operational implications in the purchasing management. To this purpose, the course presents purchasing strategies of item categories, purchasing portfolio matrices and spending analysis of organizations. Then, the course describes the steps of the procurement process and examines in-depth the operational aspects of the keys underlying activities.
After completing this course, the student will master some methodological tools that will enable him to elaborate an appropriate purchasing strategy of a specific item category, to assess and select reliable and efficient providers, and to obtain terms and conditions that are responsive to the buyer firm needs.

Educational objectives

GENERAL OBJECTIVES
The course aims to provide students with a basic understanding of concepts and tools relevant to Innovation Management. Specifically, the course aims to help students understand: the forms, models, and sources of innovation; standard conflicts and the definition of dominant design; market entry timing choices; innovation protection mechanisms; the process of developing a new product; the integration of environmental sustainability into marketing strategy and new product development. Furthermore, through the analysis of a series of case studies, the course aims to develop students' critical analysis skills, enabling them to interpret and explain business behavior and outcomes within the context of technological innovation strategies in light of the concepts learned during the course.

SPECIFIC OBJECTIVES
KNOWLEDGE AND UNDERSTANDING. The course will enable students to acquire knowledge and understanding of the main concepts and fundamental tools of Innovation Management. Students will learn to recognize and master best practices and success factors of Innovation Management and apply them in real-world contexts.

APPLICATIVE SKILLS. Thanks to the course, students will be able to critically evaluate an enterprise's technological innovation strategies, as well as classify products based on their environmental impact.

JUDGMENT AUTONOMY. The course will empower students to choose, given the main environmental forces, the characteristics of the enterprise and innovation, the best technological innovation strategies. Additionally, students will develop the ability to critically analyze innovation management.

COMMUNICATION SKILLS. By the end of the course, students will be able to illustrate concepts of innovation management using internationally established terminology and models, organize information and data in a format and reporting process understandable to professionals.

LEARNING ABILITY. Students will develop independent study skills and critical understanding and evaluation of marketing and technological innovation strategies and related tools

Educational objectives

The course is aimed at the creation of a knowledge-base in the student on the main processing technologies, typical of metallic materials, in use or expected to be adopted in the manufacturing industry. This course aims also to provide some case studies of typical industrial applications which analyze specific technological aspects and limitations in order to give a technical-practical qualification to the student and solid knowledge of tools that will enable him to understand technological problems, to work by making innovations and structuring its actions in a logical way, developing capacity also strongly requested by companies.Autonomy of judgment: Evaluate and compare the performance expected by the employment of different manufacturing technologies to scenarios which are different from the usual one, elaborating solutions on the basis of known information. Communicative skills: to be able to communicate clearly their own conclusions on issues concerning topics which are objet of the course and on topics concerning the performance of manufacturing processes.

Educational objectives

OBJECTIVES
The course aims to provide the basic knowledge of Quality in process management for organizations, through the definition and historical evolution of the concept (from Quality Control to Total Quality Management), the regulatory framework, methodologies for analysis and improvement. In particular, the course presents an applicative focus on process mapping and management and on Lean Six Sigma.

EXPECTED LEARNING OUTCOMES
Knowledge and understanding: in-depth knowledge of terminology and reference concepts for quality management, knowledge of the principles of Lean Manufacturing and knowledge of the Lean Six Sigma methodology. Capability: ability to develop analysis and mapping of processes for value generation and identification of waste from a Lean perspective, ability to set up and develop a project according to the requirements of the Lean Six Sigma methodology, through the application of all phases of DMAIC, identifying appropriate performance measurement tools and defining objectives and improvement programs.

Educational objectives

Gain cognitive and technical tools for statistical process control.Acquire methodologies of design of experiments for process improvementGain tools for acceptance sampling of a lotRisultati di apprendimento attesi (Inglese):Student must be able to:- plan and execute a statistical process control by control charts- plan a experiments campaign in order to achieve a technological model of a process- design a lot acceptance control

Educational objectives

This course aims providing knowledges and abilities in the field of Additive Manufacturing with regards to:

- Knowledge about several technologies by means of physical and chemical processes;

- Knowledge about design methods applied to the virtual model and its reparing;

- Ability to manage different processes choosing suitable parameters and fabrication strategies;

- Ability to plan, before the AM fabrication, post processing operation in order to comply with the design requirements;

- Ability to compare additive and traditional processes in order to choose the better one for a specific case;

- Ability to apply the acquired knowledges to case studies;

- Ability to provide a technological transfer.

Educational objectives

To realize the knowledge for design and management of safety and maintenance in industrial complex systems.

Educational objectives

OBJECTIVES. The course aims to provide the knowledge bases of the Smart Factories in the context of Industry 4.0 which is characterized as the Fourth Industrial Revolution through the analysis of the economic and technological scenario, the identification and classification of intervention key areas, the processes for a strategy 4.0 implementation, the definition of organizational models, the identification of design and management issues.
EXPECTED LEARNING OUTCOMES. Knowledge and understanding: Knowledge of the structural and operating characteristics of Smart Factories within the framework of Industry 4.0. Applying knowledge and understanding: Ability to develop analysis, model problems and identify best techniques for implementing Smart Production in a Smart Factory. The course requires preparation of a technical report (usually prepared in small working groups self-managed by students); the course also aims to promote the development of skills to apply the knowledge acquired through independent learning and teamworking, making independent judgment and communication skills.

Educational objectives

Gain cognitive and technical tools for statistical process control.Acquire methodologies of design of experiments for process improvementGain tools for acceptance sampling of a lotRisultati di apprendimento attesi (Inglese):Student must be able to:- plan and execute a statistical process control by control charts- plan a experiments campaign in order to achieve a technological model of a process- design a lot acceptance control

Educational objectives

This course aims providing knowledges and abilities in the field of Additive Manufacturing with regards to:

- Knowledge about several technologies by means of physical and chemical processes;

- Knowledge about design methods applied to the virtual model and its reparing;

- Ability to manage different processes choosing suitable parameters and fabrication strategies;

- Ability to plan, before the AM fabrication, post processing operation in order to comply with the design requirements;

- Ability to compare additive and traditional processes in order to choose the better one for a specific case;

- Ability to apply the acquired knowledges to case studies;

- Ability to provide a technological transfer.

Educational objectives

The course aims to describe the founding principles, the scope and the fundamental toolsand
methodologies of project management and of organizational processes.
Starting from the concept of integrated management of projects, all the
main methods for managing the performance variables of quality, time and
cost will be proposed. In line with the main standard processes of
project management the internationally standardized project management
terminology will be used. The course also intends to present the
principles and techniques of business process re-engineering and
management.Risultati di apprendimento attesi (Inglese):At the
end of the course the student will be able to plan a project starting
from the objectives of quality, time and cost defined by internal or
external customers of a company. She/he will also be able to critically
analyze an ongoing project proposing both organizational and managerial
improvements and both the use of correct project management
methodologies.

Educational objectives

The specific aim is to allow the student to use and expand the bulk of knowledge acquired during the course of study performing some activities in an industrial setting, a company, or a research laboratory.

Educational objectives

The course gives on-field experience of Operations Management, from an operational and technical point of view. The course develops one of the main topics of Operations Management, e.g. company-market relations, supply chain management, production and inventory management.

EXPECTED LEARNING OUTCOMES. Knowledge and understanding: Deepening and consolidation of the knowledge provided in the Operations Management course. Capability: Expected learning outcomes include the ability to develop analyses, model problems, and identify the best techniques for solving major characteristic problems in production management, materials management, logistics management, and supply chain management through project work and on-field experience.

Educational objectives

Main course’s objective is
developing digital competences to make citizens able to use Information
and Communication Technologies (ICT) at work, in day-to-day relationships, in
dealing with public services as well as in culture, entertainment, leisure and
when participating in community and political dialogues. This course contributes
to actualize the EU i2010 program “increasing social
inclusion through reducing digital divide to build a society for
all”. The course promotes ICT use also to put in action the Italian Digital
Administration Low as well as the ICT right use (art.3) and the Public
Administration Data Availability (art 50 capo V).

Educational objectives

The objective is to provide the management engineer with the basis for understanding the theory and principles of innovative optical, photothermal, photoacoustic, radiometric and thermographic techniques and instruments, and to understand the main applications together with their industrial relapses and with a deep analysis of the economical impacts and parameters.

The topics are organized to provide scientific technical expertise in order to work in the field of applied research, making easier the employment of the new engineer in industry.

Contents of the proposed course:

The course will provide the theoretical bases of the optical systems, the laser with its applications. Photothermal, photoacoustic, radiometric, and infrared techniques will be introduced for nonsdestructive evaluation and testing of materials, together with the many applications in different fields: industry, environment, energy, but also biology, medicine, and in the emerging sector of agri-food. Final comparisons will be introduced among the diagnostic techniques by using parameters of the management engeneering. The course contains also some experimental activities in laboratory and the data analysis and processing.

Educational objectives

The course aims at deepening the design, the implementation, the execution and the analysis of the results of
discrete event simulation models. Particular focus will be on the use of specialized software packages and languages
for discrete event simulation and their possible use in connection with optimization software. Students will be
directly involved in laboratory activities and in particular in the implementation of real case studies.

Knowledge and understanding:
Techniques for implementing a discrete event simulation model. Use of software packages dedicated to
discrete event simulation and their possible integration with optimization software.

Applying knowledge and understanding:
To be able to carry out a complete study of a real problem through discrete event simulation, from the preliminary analysis
of the processes, the implementation, up to the interpretation of the results.

Making judgements:
Knowing how to identify the fundamental characteristics of a real process for the construction of a model of
discrete event simulation. Knowing how to evaluate the impact of the output of a simulation on the real case in analysis.

Communication skills:
The laboratory activities will allow the student to learn communicating and sharing simulation models and their outputs.

Learning skills:
The laboratory activities will stimulate the students to the autonomous realization of simulation models, to teamwork,
and to the concrete application of the techniques learned in the course.

Educational objectives

The specific goal of these activities is to enable the students to merge their academic knowledge with professional skills.

Educational objectives

GENERAL OBJECTIVES

The course aims to give students the basic tools to understand the strategic role that the green economy and bioeconomy will have in the transition of economic systems towards the goals of sustainability in order to provide a proper balance of ecosystems. The production, storage and sustainable distribution of energy are a goal to be pursued towards the decarbonisation of energy systems. To this end, it will be essential to provide knowledge about the mechanisms of operation and regulation of the energy value chain. The complexity of the issues addressed requires an interdisciplinary approach in which economic and managerial analysis will play a key role.

SPECIFIC OBJECTIVES

Knowledge and understanding
The program aims to provide the basic skills of models and methodologies suitable to extend and integrate the understanding of the interfaces and interaction between ecosystems and the economy with a particular focus on the energy sector including regulatory systems.

Applying knowledge and understanding
The student will have gained the basic knowledge necessary to understand the issues of resource management from a sustainable perspective and will be able to contribute both within research centres, institutions and international organizations, as well as in the private sector that shows a growing attention to management issues that can propose solutions to climate change. The student will be able to frame and plan investments in policy scenarios ensuring a sustainable business in the long term.

Making judgements
The course aims to provide a dual training both theoretical, such as to make the student able to evaluate data and information obtained through databases and scientific literature of reference and managerial, such as to apply the methodologies to real case studies. The economic-financial tools of the energy business will allow defining the optimal use of resources also considering the regulatory aspects of the energy sector.

Communication skills
The student will be able to expose new concepts of economics and management of energy sources and services knowing the specific terminology of reference. Based on the concepts and models presented in the course she/he will expand her/his view on sustainable development models and understand how the public and private sectors economically evaluate green economy and bioeconomy models. The student will be able to provide synthesis results that consider the different perspectives of analysis.

Educational objectives

General objectives

The Environmental Economics and Management course is aimed at providing students with the basic knowledge concerning the complex relationships between the economic system and the environment. To this aim, the course is aimed at discussing with students that the current linear economic model “take-make-dispose” is no more sustainable, given the strong environmental constraints that our society must tackle, as well as the main policy and business strategies aimed at favoring the transition towards the circular economic model, able to respect the above-mentioned environmental constraints.
The main topics addressed during the class are the following: theories and evidences related to climate change; relationships between economic system and the environment; international agreements and policy measures related to the environment; production-based and consumption-based environmental accounting, with particular focus on climate and energy; principles of circular economy; industrial ecology and industrial symbiosis; sustainable supply chain management.
Through the analysis of case studies, the course is aimed to provide students with the critical ability to interpret the companies’ behavior towards the circular economy, design new sustainable and circular business models, and reconvert the current business models according to the principles of circular economy.

Specific objectives

Knowledge and understanding: The course allows students to know the main managerial strategies supporting the company’s transition towards the circular economy.

Apply knowledge and understanding: Students will be able to design circular business models and sustainable business models, also thanks to the experience of project work. At the end of the course, students will be able to assess how much a given business model is sustainable.

Critical and judgment skills: Students will be able to assess ex ante the implications – from the economic, social, and environmental perspective – of a given circular business model.

Communication skills: At the end of the course, students will be able to discuss the topics addressed during the class by using the consolidated terminology, both from the scientific and the managerial perspective.

Learning ability: Students will develop the autonomous ability to study and critically assess the business choices of companies. The use of business games for some topics of the class will allow students to learn by doing.

Educational objectives

The course aims to introduce students to the reasons economic government intervention in the economy and the relevance of the presence of the public sector in economics advanced, offering the main models and institutional knowledge of the European and national level.
The course aims to make the student capable of reading and interpret the evolution of the public sector in our country and his major structural reform in the coming years, well also in order to seize the potential opportunities.

Educational objectives

General objectives
The course combines practical sessions and exercises to introduce the main data analysis techniques (including supervised and unsupervised learning techniques) and operational tools (including R, Excel and generative AI) available for developing data analyses to support 'business activities'. Each technique presented will be accompanied by at least one case study, presented through interactive lab sessions.
More precisely, the general objectives of the course are:
• Present an overview of the role of the Data Analyst and the objectives of the possible analyses to be implemented (business purpose).
• To introduce the main software available for the implementation of the analysis techniques presented during the course.
• Present the operational use of generative AI tools for data analysis.
• Present the basic techniques for data mining and scraping and text analysis.
• Present the implementation of estimation, time series and clustering techniques.
• Provide laboratory sessions for the practical implementation of the techniques presented during the course.
• Present various applications in the field of economics and management as potential group work, to be developed by students according to their personal interests and backgrounds.
• Provide the rudiments of data presentation and data storytelling with advanced operational tools (such as shiny or powerBI-based platforms).
• To interact with students through assisted workshops, oral presentations and the realization of a project on real data.

Specific objectives
• Knowledge and understanding: demonstrate knowledge of developing data analysis techniques;
• Apply knowledge and understanding: apply specific software tools to develop data analysis techniques;
• Critical and judgment skills: be able to evaluate data sources to be used critically and independently, subsequently choosing the appropriate analysis method and implementing it correctly;
• Communication skills: be able to communicate analysis results and related information to different types of interlocutors;
• Learning ability: develop the skills necessary to independently apply and develop the various techniques learned during the course.

Educational objectives

The course introduces to the nonlinear continuous optimization problems and describes the main methodological approaches to efficiently solve this class of optimization problems.

At the end of the course, the student should be able to identify the most suitable methodological approach to tackle the real problem to be solved [A) knowledge and understanding]. The student should also be able to correctly use the software available in literature and/or to realize new codes for solving nonlinear continuous optimization problems [B) applying knowledge and understanding]. The student should also have the ability to integrate the mathematical tools proposed in the course to tackle complex real problems [ C) making judgements]. The student should also show that he / she is able to communicate and transfer the methodological approaches used in the considered problems [ D) communication skills]. Finally, the student should have learned well the concepts and methodologies proposed in the course that allow him / her to independently deep further methodological developments of Continuous Optimization [ E) learning skills].
The skills achieved by the student will be verified by a written exam.

Educational objectives

ENG
GENERAL OBJECTIVES
The course aims to provide students with a fundamental understanding of concepts and tools relevant to marketing. Specifically, the course aims to help students understand: the main forces of the marketing environment; the marketing information system; consumer and business buying behaviors; the stages and tools for formulating and implementing a marketing strategy. Furthermore, through the analysis of a series of case studies, the course aims to develop students' critical analysis skills, enabling them to interpret and explain business behavior and outcomes within marketing strategies in light of the concepts learned during the course.

SPECIFIC OBJECTIVES
KNOWLEDGE AND UNDERSTANDING. The course will enable students to acquire knowledge and understanding of the main concepts and fundamental tools of Marketing. Students will learn to recognize and master best practices and success factors of Marketing and apply them in real-world contexts.

APPLICATIVE SKILLS. Thanks to the course, students will be able to formulate a marketing plan, as well as critically evaluate marketing strategies.

JUDGMENT AUTONOMY. The course will empower students to choose, given the main environmental forces, the characteristics of the enterprise and innovation, the best marketing strategies. Additionally, students will develop the ability to critically analyze marketing.

COMMUNICATION SKILLS. By the end of the course, students will be able to explain marketing concepts using internationally established terminology and models, organize information and data in a format and reporting process understandable to professionals.

LEARNING ABILITY. Students will develop independent study skills and critical understanding and evaluation of marketing strategies and related tools.

Educational objectives

OBJECTIVES
The course aims to provide the basic knowledge of Quality in process management for organizations, through the definition and historical evolution of the concept (from Quality Control to Total Quality Management), the regulatory framework, methodologies for analysis and improvement. In particular, the course presents an applicative focus on process mapping and management and on Lean Six Sigma.

EXPECTED LEARNING OUTCOMES
Knowledge and understanding: in-depth knowledge of terminology and reference concepts for quality management, knowledge of the principles of Lean Manufacturing and knowledge of the Lean Six Sigma methodology. Capability: ability to develop analysis and mapping of processes for value generation and identification of waste from a Lean perspective, ability to set up and develop a project according to the requirements of the Lean Six Sigma methodology, through the application of all phases of DMAIC, identifying appropriate performance measurement tools and defining objectives and improvement programs.

Educational objectives

This course aims at addressing important strategic aspects and operational implications in the purchasing management. To this purpose, the course presents purchasing strategies of item categories, purchasing portfolio matrices and spending analysis of organizations. Then, the course describes the steps of the procurement process and examines in-depth the operational aspects of the keys underlying activities.
After completing this course, the student will master some methodological tools that will enable him to elaborate an appropriate purchasing strategy of a specific item category, to assess and select reliable and efficient providers, and to obtain terms and conditions that are responsive to the buyer firm needs.

Educational objectives

General outcomes:

The course will present a broad survey of topics at the interface of computer
science, data science, and economics, emphasizing efficiency, robustness, and application to emerging online markets. It will introduce the principles of algorithmic game theory and mechanism design, algorithmic market design, as well as machine learning in games and markets. It will demonstrate applications to case studies in Web search and advertising, network economics, Data, cryptocurrency, and AI markets.

Specific outcomes:
Knowledge and understanding:
The algorithmic and mathematical economics principles underlying the design and the operation of efficient and robust online markets. The application of these principles in concrete examples of online markets.

Applying knowledge and understanding:
Being able to design and analyze algorithms for concrete online market applications with respect to the requirements of efficiency and robustness.

Making judgements:
Being able to evaluate the quality of an algorithm for online market applications, discriminating the modeling aspects from those related to algorithmic and system implementation.

Communication skills:
Ability to communicate and share the modeling choices and system requirements, as well as the results of the analysis of the efficiency of online market algorithms.

Learning skills:
The course stimulates the students to acquire learning skills at the crossroads of computer science, economics, and digital market applications, including the different languages used in these fields.

Educational objectives

GENERAL OBJECTIVES
The course aims to provide students with a basic understanding of concepts and tools relevant to Innovation Management. Specifically, the course aims to help students understand: the forms, models, and sources of innovation; standard conflicts and the definition of dominant design; market entry timing choices; innovation protection mechanisms; the process of developing a new product; the integration of environmental sustainability into marketing strategy and new product development. Furthermore, through the analysis of a series of case studies, the course aims to develop students' critical analysis skills, enabling them to interpret and explain business behavior and outcomes within the context of technological innovation strategies in light of the concepts learned during the course.

SPECIFIC OBJECTIVES
KNOWLEDGE AND UNDERSTANDING. The course will enable students to acquire knowledge and understanding of the main concepts and fundamental tools of Innovation Management. Students will learn to recognize and master best practices and success factors of Innovation Management and apply them in real-world contexts.

APPLICATIVE SKILLS. Thanks to the course, students will be able to critically evaluate an enterprise's technological innovation strategies, as well as classify products based on their environmental impact.

JUDGMENT AUTONOMY. The course will empower students to choose, given the main environmental forces, the characteristics of the enterprise and innovation, the best technological innovation strategies. Additionally, students will develop the ability to critically analyze innovation management.

COMMUNICATION SKILLS. By the end of the course, students will be able to illustrate concepts of innovation management using internationally established terminology and models, organize information and data in a format and reporting process understandable to professionals.

LEARNING ABILITY. Students will develop independent study skills and critical understanding and evaluation of marketing and technological innovation strategies and related tools

Educational objectives

1) Knowledge and understanding
During the lessons of Data-driven Economics, students acquire the basic theoretical elements of econometric analysis. Theoretical lessons are aimed at guiding students in the acquisition of the basics of simple and multiple regression models, starting from the relative assumptions, and then proceeding with the estimation and inference procedures. The course contents cover both the estimation of linear and non-linear models and the analysis of both cross-sectional and longitudinal data.
2) Applicate applying knowledge and understanding
The students of the Data-driven Economics course are able to apply the notions acquired during the theoretical lessons to a wide range of problems of an empirical nature. They acquire the ability to build econometric models aimed at giving empirical content to economic relations and are also able to establish a causal link between two or more variables in the economic field.
3) Making judgements
Students are encouraged to critically discuss empirical studies published in the economic/managerial field in the classroom. The Data-driven Economics course also includes a laboratory in which students apply the acquired knowledge of econometrics to the estimation of empirical models carried out using data made available by the teacher.
4) Communication skills
At the end of the course, students are able to illustrate and explain the strengths and weaknesses of a wide range of empirical methodologies to a variety of heterogeneous interlocutors in terms of training and professional role. The acquisition of these skills is verified and evaluated not only during the final exam, by means of a written test and a possible oral test, but also during flipped class sessions in which, individually or in groups, students are called to present empirical studies published in the economic/managerial field.
5) Learning skills
Students acquire the ability to independently conduct empirical analyses by building econometric models to be estimated using data with diversified structures. The tools provided by the course allow for the analysis of systems in which a large number of factors simultaneously contribute to explaining their states and impact assessments that take into account the uncertainty and risk inherent in the application of policies. The acquisition of these skills is verified and evaluated on during the final exam, by means a written test and a possible oral test, in which the student can be called to discuss empirical problems on the basis of the topics covered and the reference material distributed during the course.

Educational objectives

The purpose of this course is to study mathematical models useful in taking decisions when more than a decision maker is present.
In particular variational inequalities and game theoretic models will be analyzed in detail. Emphasis will be given to computational aspects.
At the end of the course the student will be able to cast equilibrium problems as variational inequalities or by using game models and to develop suitable solution algorithms. He/She will also learn how to use game theoretic models and how to find algorithmically their equilibria and in realistic cases.

Knowledge and understanding
The aim of the course is to give students a basic knowledge of analytic methods for multi-agent environments analysis.
Students will be able to model mathematically complex interactions among (economic) agents and to analyze the consequences of different choices.

Applying knowledge and understanding
By the end of the course students will be able apply analytical tools to the analysis of economic and industrial settings.

Making judgements
Lectures and practical exercises will provide students with the ability toassess the main strengths and weaknesses of the learned theoretical models.
Students will also be able to gauge consequences of different decisionswhen using multi agent models.

Communication
By the end of the course, students will be able to discuss relevant information, ideas, problems and solutions both with a specialized and a non-specialized audience.

Lifelong learning skills
Students are expected to develop those learning skills necessary to undertake additional studieson the relevant topics with a high degree of autonomy. During the course, students are encouraged to investigate further topics of major interest by consulting supplementary academic publications, specialized books, and internet sites.

Educational objectives

General Objectives of the course

The course, with an interdisciplinary approach, combines theoretical lectures on the economics of production, with lectures on the main econometric approaches proposed in the literature, including recent developments, and practical sessions to introduce to the main open source software available to carry out productivity and efficiency analysis.
The main objectives of the course are:
- Present a general overview on the economic theory of productivity and efficiency;
- Propose a unified framework on the main methodologies available to estimate and compare productivity and efficiency of Decision Making Units (DMUs);
- Make an introduction to the main open source software available to estimate productivity and efficiency;
- Provide laboratory sessions to implement productivity and efficiency analyses in practice;
- Provide the basic concepts to analyse the specialised literature;
- Interact with students through assisted laboratory and the realization of a practical work on real data, seminars and oral presentations.

Specific Objectives
• KNOWLEDGE AND UNDERSTANDING: DEMONSTRATE THE KNOWLEDGE OF THE BASIC ELEMENTS OF PRODUCTIVITY AND EFFICIENCY ANALYSIS;
• ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING: TO BE ABLE TO APPLY EFFICIENCY ANALYSIS TECHNIQUES LEARNED DURING THE COURSE IN ITS OWN ENGINEERING AREA OF SPECIALIZATION;
• JUDGMENT AUTONOMY: TO BE ABLE TO PERFORM AN EFFICIENCY ANALYSIS WITH CRITICAL SPIRIT, CHOOSING THE APPROPRIATE METHOD AND CORRECTLY IMPLEMENTING IT.
• COMMUNICATION SKILLS: BEING ABLE TO COMMUNICATE THE RESULTS OF THE ANALYSIS AND ITS INFORMATION TO DIFFERENT TYPES OF INTERLOCUTORS;
• LEARNING SKILLS: TO DEVELOP THE NECESSARY SKILLS TO APPLY AND DEVELOP AUTONOMOUSLY THE METHODS LEARNED DURING THE COURSE.

Educational objectives

Knowledge and understanding
The course introduces students to the economics and management of networks. On the one hand, the course illustrates the main features of the new information economy, and discusses the prevailing and emerging business models. On the other hand, it explores competition and regulation issues in liberalized network industries, such as telecommunications, energy, and transportation.

Applying knowledge and understanding
Students are expected to be able to use methods and models of microeconomics and industrial organization to understand and analyze the impact of technology and demand on market structure, firms’ strategies and business models in the new information economy. They will also gain insight on the rationale and the scope for public policy in network industries.

Making judgements
Lectures, practical exercises and problem-solving sessions will provide students with the ability to assess the main strengths and weaknesses of theoretical models when used to explain empirical evidence and case studies in the new information economy and in network industries.

Communication
By the end of the course, students are able to point out the main features of the new information economy and network industries, and to discuss relevant information, ideas, problems and solutions both with a specialized and a non-specialized audience. These capabilities are tested and evaluated in the final written exam and possibly in the oral exam as well as in the project work.

Lifelong learning skills
Students are expected to develop those learning skills necessary to undertake additional studies on relevant topics in the field of the new information economy and network industries with a high degree of autonomy. During the course, students are encouraged to investigate further any topics of major interest, by consulting supplementary academic publications, specialized books, and internet sites. These capabilities are tested and evaluated in the final written exam and possibly in the oral exam as well as in the project work, where students may have to discuss and solve some new problems based on the topics and material covered in class.

Educational objectives

ENG
GENERAL OBJECTIVES
The course aims to provide students with a fundamental understanding of concepts and tools relevant to marketing. Specifically, the course aims to help students understand: the main forces of the marketing environment; the marketing information system; consumer and business buying behaviors; the stages and tools for formulating and implementing a marketing strategy. Furthermore, through the analysis of a series of case studies, the course aims to develop students' critical analysis skills, enabling them to interpret and explain business behavior and outcomes within marketing strategies in light of the concepts learned during the course.

SPECIFIC OBJECTIVES
KNOWLEDGE AND UNDERSTANDING. The course will enable students to acquire knowledge and understanding of the main concepts and fundamental tools of Marketing. Students will learn to recognize and master best practices and success factors of Marketing and apply them in real-world contexts.

APPLICATIVE SKILLS. Thanks to the course, students will be able to formulate a marketing plan, as well as critically evaluate marketing strategies.

JUDGMENT AUTONOMY. The course will empower students to choose, given the main environmental forces, the characteristics of the enterprise and innovation, the best marketing strategies. Additionally, students will develop the ability to critically analyze marketing.

COMMUNICATION SKILLS. By the end of the course, students will be able to explain marketing concepts using internationally established terminology and models, organize information and data in a format and reporting process understandable to professionals.

LEARNING ABILITY. Students will develop independent study skills and critical understanding and evaluation of marketing strategies and related tools.

Educational objectives

GENERAL OBJECTIVES
The course aims to provide students with a basic understanding of concepts and tools relevant to Innovation Management. Specifically, the course aims to help students understand: the forms, models, and sources of innovation; standard conflicts and the definition of dominant design; market entry timing choices; innovation protection mechanisms; the process of developing a new product; the integration of environmental sustainability into marketing strategy and new product development. Furthermore, through the analysis of a series of case studies, the course aims to develop students' critical analysis skills, enabling them to interpret and explain business behavior and outcomes within the context of technological innovation strategies in light of the concepts learned during the course.

SPECIFIC OBJECTIVES
KNOWLEDGE AND UNDERSTANDING. The course will enable students to acquire knowledge and understanding of the main concepts and fundamental tools of Innovation Management. Students will learn to recognize and master best practices and success factors of Innovation Management and apply them in real-world contexts.

APPLICATIVE SKILLS. Thanks to the course, students will be able to critically evaluate an enterprise's technological innovation strategies, as well as classify products based on their environmental impact.

JUDGMENT AUTONOMY. The course will empower students to choose, given the main environmental forces, the characteristics of the enterprise and innovation, the best technological innovation strategies. Additionally, students will develop the ability to critically analyze innovation management.

COMMUNICATION SKILLS. By the end of the course, students will be able to illustrate concepts of innovation management using internationally established terminology and models, organize information and data in a format and reporting process understandable to professionals.

LEARNING ABILITY. Students will develop independent study skills and critical understanding and evaluation of marketing and technological innovation strategies and related tools

Educational objectives

Gain cognitive and technical tools for statistical process control.Acquire methodologies of design of experiments for process improvementGain tools for acceptance sampling of a lotRisultati di apprendimento attesi (Inglese):Student must be able to:- plan and execute a statistical process control by control charts- plan a experiments campaign in order to achieve a technological model of a process- design a lot acceptance control

Educational objectives

This course aims providing knowledges and abilities in the field of Additive Manufacturing with regards to:

- Knowledge about several technologies by means of physical and chemical processes;

- Knowledge about design methods applied to the virtual model and its reparing;

- Ability to manage different processes choosing suitable parameters and fabrication strategies;

- Ability to plan, before the AM fabrication, post processing operation in order to comply with the design requirements;

- Ability to compare additive and traditional processes in order to choose the better one for a specific case;

- Ability to apply the acquired knowledges to case studies;

- Ability to provide a technological transfer.

Educational objectives

The course aims to describe the founding principles, the scope and the fundamental toolsand
methodologies of project management and of organizational processes.
Starting from the concept of integrated management of projects, all the
main methods for managing the performance variables of quality, time and
cost will be proposed. In line with the main standard processes of
project management the internationally standardized project management
terminology will be used. The course also intends to present the
principles and techniques of business process re-engineering and
management.Risultati di apprendimento attesi (Inglese):At the
end of the course the student will be able to plan a project starting
from the objectives of quality, time and cost defined by internal or
external customers of a company. She/he will also be able to critically
analyze an ongoing project proposing both organizational and managerial
improvements and both the use of correct project management
methodologies.

Educational objectives

The specific aim is to allow the student to use and expand the bulk of knowledge acquired during the course of study performing some activities in an industrial setting, a company, or a research laboratory.

Educational objectives

The course gives on-field experience of Operations Management, from an operational and technical point of view. The course develops one of the main topics of Operations Management, e.g. company-market relations, supply chain management, production and inventory management.

EXPECTED LEARNING OUTCOMES. Knowledge and understanding: Deepening and consolidation of the knowledge provided in the Operations Management course. Capability: Expected learning outcomes include the ability to develop analyses, model problems, and identify the best techniques for solving major characteristic problems in production management, materials management, logistics management, and supply chain management through project work and on-field experience.

Educational objectives

Main course’s objective is
developing digital competences to make citizens able to use Information
and Communication Technologies (ICT) at work, in day-to-day relationships, in
dealing with public services as well as in culture, entertainment, leisure and
when participating in community and political dialogues. This course contributes
to actualize the EU i2010 program “increasing social
inclusion through reducing digital divide to build a society for
all”. The course promotes ICT use also to put in action the Italian Digital
Administration Low as well as the ICT right use (art.3) and the Public
Administration Data Availability (art 50 capo V).

Educational objectives

The objective is to provide the management engineer with the basis for understanding the theory and principles of innovative optical, photothermal, photoacoustic, radiometric and thermographic techniques and instruments, and to understand the main applications together with their industrial relapses and with a deep analysis of the economical impacts and parameters.

The topics are organized to provide scientific technical expertise in order to work in the field of applied research, making easier the employment of the new engineer in industry.

Contents of the proposed course:

The course will provide the theoretical bases of the optical systems, the laser with its applications. Photothermal, photoacoustic, radiometric, and infrared techniques will be introduced for nonsdestructive evaluation and testing of materials, together with the many applications in different fields: industry, environment, energy, but also biology, medicine, and in the emerging sector of agri-food. Final comparisons will be introduced among the diagnostic techniques by using parameters of the management engeneering. The course contains also some experimental activities in laboratory and the data analysis and processing.

Educational objectives

The course aims at deepening the design, the implementation, the execution and the analysis of the results of
discrete event simulation models. Particular focus will be on the use of specialized software packages and languages
for discrete event simulation and their possible use in connection with optimization software. Students will be
directly involved in laboratory activities and in particular in the implementation of real case studies.

Knowledge and understanding:
Techniques for implementing a discrete event simulation model. Use of software packages dedicated to
discrete event simulation and their possible integration with optimization software.

Applying knowledge and understanding:
To be able to carry out a complete study of a real problem through discrete event simulation, from the preliminary analysis
of the processes, the implementation, up to the interpretation of the results.

Making judgements:
Knowing how to identify the fundamental characteristics of a real process for the construction of a model of
discrete event simulation. Knowing how to evaluate the impact of the output of a simulation on the real case in analysis.

Communication skills:
The laboratory activities will allow the student to learn communicating and sharing simulation models and their outputs.

Learning skills:
The laboratory activities will stimulate the students to the autonomous realization of simulation models, to teamwork,
and to the concrete application of the techniques learned in the course.

Educational objectives

The specific goal of these activities is to enable the students to merge their academic knowledge with professional skills.

Educational objectives

The course aims at illustrating the analytical foundations of the study of the Queueing systems,
which are structures characterized by random arrival of clients who request a service to be performed by a server.
The purpose is to evaluate some fundamental Key Performance Indicators in order to efficiently design the system.
The course also aims at providing the basic tools for building and using discrete event simulation models. Discrete event
simulation techniques are introduced as a tool to reproduce real processes - already existing or to be designed - through
appropriate models, in order to study the effects of possible interventions, in the first case, or to evaluate different
design and/or strategic choices in the second case.

Knowledge and understanding:
Queueing systems models and their main Key Performance Indicators. Building and validating discrete event simulation
models. Designing of experiments and executing of simulation runs.

Applying knowledge and understanding:
To be able to build and to solve queueing models. To be able to design, to execute and to assess the output of a discrete
event simulation.

Making judgements:
To be able to recognize real problems which can be modelled as queueing systems. Knowing how to identify the characteristic
elements of a real process for the construction of a simulation model. Knowing how to analyze the output of a
discrete event simulation.

Communication skills:
Course lectures and exercises should provide the student with communication and sharing skill concerning the modelling by
means of queueing systems and discrete event simulation models of real problems.

Learning skills:
In addition to the classic learning skills provided by the theoretical study of the teaching material, the course,
in particular the exercises, will stimulate the student to deepen his knowledge of some topics, to team working,
and to the concrete application of the concepts and techniques learned in the course.

Educational objectives

The course
is intended to develop the capacity of formulating the optimization
problems underlying several design activities; to give the information
able to select suitable algorithms for the problem solution; to develop
new algorithms better performing than the available ones.

Educational objectives

The purpose of this course is to study mathematical models useful in taking decisions when more than a decision maker is present.
In particular variational inequalities and game theoretic models will be analyzed in detail. Emphasis will be given to computational aspects.
At the end of the course the student will be able to cast equilibrium problems as variational inequalities or by using game models and to develop suitable solution algorithms. He/She will also learn how to use game theoretic models and how to find algorithmically their equilibria and in realistic cases.

Knowledge and understanding
The aim of the course is to give students a basic knowledge of analytic methods for multi-agent environments analysis.
Students will be able to model mathematically complex interactions among (economic) agents and to analyze the consequences of different choices.

Applying knowledge and understanding
By the end of the course students will be able apply analytical tools to the analysis of economic and industrial settings.

Making judgements
Lectures and practical exercises will provide students with the ability toassess the main strengths and weaknesses of the learned theoretical models.
Students will also be able to gauge consequences of different decisionswhen using multi agent models.

Communication
By the end of the course, students will be able to discuss relevant information, ideas, problems and solutions both with a specialized and a non-specialized audience.

Lifelong learning skills
Students are expected to develop those learning skills necessary to undertake additional studieson the relevant topics with a high degree of autonomy. During the course, students are encouraged to investigate further topics of major interest by consulting supplementary academic publications, specialized books, and internet sites.

Educational objectives

Knowledge and understanding
The aim of the course is to introduce students to the application of optimization techniques to training problems arising in machine learning. Students are expected to gain insight into standard models in Machine Learning (Deep Networks and Support Vector Machines) and into more recent optimization algorithms for determining the parameters (training) of such models that best fit to the available data.

Applying knowledge and understanding
By the end of the course, students should be able to select the correct model for the problem at hand and either to use standard software specialized to the application and/or to develop their own optimization algorithm.
modelli di apprendimento automatico applicati ai casi studio in apprendimento automatico.

Making judgements
Lectures, practical exercises and project sessions will provide students with the ability to assess the main strengths and weaknesses of the different machine learning models applied to case studies in machine learning.

Communication
By the end of the course, students are able to point out the main features of a machine learning problem and explain techniques for its solution both with a specialized and a non-specialized audience. These abilities are tested and evaluated in the projects developed in small groups thus encouraging team building and a proactive learning process coupling with collaborative learning. These abilities can also be checked in the final oral exam.

Lifelong learning skills
Students are expected to develop those learning skills necessary to undertake additional studies on the relevant topics with a high degree of autonomy. During the classes, students are encouraged to work on projects into small groups thus stimulating student activity and engagement. They are pushed to consult supplementary research publications and internet sites to exploit tricks and detailed choices needed to accomplish the tasks effectively. These capabilities are tested and evaluated in the development of the final reports of the projects where students have to discuss the main issues of the addressed problems and their choices to overcome the difficulties, based on the topics and material covered in class.

Educational objectives

To provide some fundamental concepts of probability and statistics and to introduce some stochastic models for finance. Trying to enable the students to refine their critical aptitudes, to render them able to face not only "routine" problems, but also any "new" matter or situation.

Educational objectives

Knowledge and understanding
The course introduces students to the economics and management of networks. On the one hand, the course illustrates the main features of the new information economy, and discusses the prevailing and emerging business models. On the other hand, it explores competition and regulation issues in liberalized network industries, such as telecommunications, energy, and transportation.

Applying knowledge and understanding
Students are expected to be able to use methods and models of microeconomics and industrial organization to understand and analyze the impact of technology and demand on market structure, firms’ strategies and business models in the new information economy. They will also gain insight on the rationale and the scope for public policy in network industries.

Making judgements
Lectures, practical exercises and problem-solving sessions will provide students with the ability to assess the main strengths and weaknesses of theoretical models when used to explain empirical evidence and case studies in the new information economy and in network industries.

Communication
By the end of the course, students are able to point out the main features of the new information economy and network industries, and to discuss relevant information, ideas, problems and solutions both with a specialized and a non-specialized audience. These capabilities are tested and evaluated in the final written exam and possibly in the oral exam as well as in the project work.

Lifelong learning skills
Students are expected to develop those learning skills necessary to undertake additional studies on relevant topics in the field of the new information economy and network industries with a high degree of autonomy. During the course, students are encouraged to investigate further any topics of major interest, by consulting supplementary academic publications, specialized books, and internet sites. These capabilities are tested and evaluated in the final written exam and possibly in the oral exam as well as in the project work, where students may have to discuss and solve some new problems based on the topics and material covered in class.

Educational objectives

###################
General Objectives:
###################

Major advances in technology have resulted in the widespread implementation of information systems into businesses and organizations.

This course introduces languages, principles and methods of process modeling, analysis and innovation as critical factors to the
overall success of a business.

The course centers around the role of conceptual (sometimes referred as business) process modeling as a means to understand and capture the
workflows of interest in information systems of various kind. Students will learn the elements of process models and their precise meaning
using the Business Process Model and Notation (BPMN) international standard.

The course will cover processes within organizations (process orchestrations) and also interacting processes involving several organizations
(process choreographies), and will look at techniques to analyze and improve such processes from a formal perspective.

The course will also provide a basic knowledge and understanding of how to design, test and implement information systems for executable processes.

Finally, the course will present methods and tools to properly use process mining techniques, which enable to discover process models (whose structure
is unknown at the outset) starting from the logs recording the concrete events executed by the real workflows.

####################
Specific Objectives:
####################

----------------------------
Knowledge and understanding:
----------------------------
At the end of the course, the students:
- learn the main methods to carry out a BPM (Business Process Management) project;
- are able to model a process with the BPMN standard;
- are able to implement and execute a process through a real information system;
- understand process mining algorithms and techniques.

-------------------------------------
Applying knowledge and understanding:
-------------------------------------
The students will be able to use suitable methodological and technological solutions for
(i) modeling a process in BPMN;
(ii) analysing it with quantitative techniques;
(iii) executing and monitoring it with an information system.

------------------
Making judgements:
------------------
The student acquires autonomy of judgment in proposing the most suitable approach to carry out a BPM project.

--------------
Communication:
--------------
The project activities and the lectures of the course allow the students to develop the proper abilities to communicate/share the design choices and
development methods for realizing any step of the business process life-cycle.

-------------------------
Lifelong learning skills:
-------------------------
In addition to the traditional learning skills provided by studying the teaching material, the project activities stimulate the student to
deepen her knowledge of the BPM topic, to improve the teamwork, and to the concrete application of the concepts and techniques investigated
during the course.

Educational objectives

KNOWLEDGE AND UNDERSTANDING.
Through the introduction of the fundamentals on the theoretical, technical and practical aspects in the design and implementation of machine learning systems for the solution of problems regarding the analysis of signals, measurements and, more generally, of big data, based on Computational Intelligence techniques such as Bayesian learning, neural networks, fuzzy logic, evolutionary algorithms, etc., the student will reinforce the knowledge acquired in the first cycle of studies. The applications in Industrial Engineering for the solution of supervised and unsupervised problems, in particular regarding optimization, approximation, regression, interpolation, prediction, filtering, pattern recognition and classification, in order to elaborate and apply orginal ideas, will be further investigated also in a research context.

CAPABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING.
Capability to analyze and solve problems related to the design, implementation and testing of machine learning algorithms, with particular reference to the development in Matlab/Python/TensorFlow environment, for developing machine learning solutions applied to problems of Industrial Engineering in the management, electrical, mechanical, logistics, biomedical fields and for the training of professional and business skills able to relate in the technical-scientific field of data analytics and business intelligence, in a context therefore broader than the field of Industrial Engineering.

MAKING AUTONOMOUS JUDGEMENTS.
The main goal of the course is to allow the student to develop machine learning systems through an appropriate formulation of the problem, a good choice of algorithms suitable for solving the problem and performing experiments in laboratory activities in order to evaluate the efficacy of the proposed solution. During the course, the main concepts and ideas that allow the effective use of machine learning algorithms in industrial applications, rather than their purely mathematical formulation, will be mainly exposed. Therefore, the student will integrate the acquired knowledge to manage the complexity of an inductive learning mechanism where new knowledge is extracted and oriented to the solution of applicatiion problems, starting from the limited information due to the organizational contingency of the course.

COMMUNICATE SKILLS.
The topics covered in the course are of general interest in the scientific and industrial fields, in particular in the analysis of materials, in the design of devices and circuits, in automation and control systems, in the inversion of physical and abstract models for decision-making processes, in the management of complex networks (smart grids, energy and freight distribution, biological and social networks, etc.). Nonetheless, applications of new technologies will be introduced in the development of innovative computing systems, primarily quantum computers, in which the use of computational intelligence and machine learning algorithms for the effective and cutting-edge exploitation of the same ones is essential. Following this course, the student will be able to communicate the knowledge acquired to specialists and non-specialists in the world of work and research, where she/he will develop the subsequent scientific and/or professional activities.

LEARNING SKILLS.
The didactic methodology implemented in the course requires an autonomous and self-managed activity of study during the development of vertical homeworks for the didactic and/or experimental investigation of some specific topics.

Educational objectives

General Objectives of the course

The course, with an interdisciplinary approach, combines theoretical lectures on the economics of production, with lectures on the main econometric approaches proposed in the literature, including recent developments, and practical sessions to introduce to the main open source software available to carry out productivity and efficiency analysis.
The main objectives of the course are:
- Present a general overview on the economic theory of productivity and efficiency;
- Propose a unified framework on the main methodologies available to estimate and compare productivity and efficiency of Decision Making Units (DMUs);
- Make an introduction to the main open source software available to estimate productivity and efficiency;
- Provide laboratory sessions to implement productivity and efficiency analyses in practice;
- Provide the basic concepts to analyse the specialised literature;
- Interact with students through assisted laboratory and the realization of a practical work on real data, seminars and oral presentations.

Specific Objectives
• KNOWLEDGE AND UNDERSTANDING: DEMONSTRATE THE KNOWLEDGE OF THE BASIC ELEMENTS OF PRODUCTIVITY AND EFFICIENCY ANALYSIS;
• ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING: TO BE ABLE TO APPLY EFFICIENCY ANALYSIS TECHNIQUES LEARNED DURING THE COURSE IN ITS OWN ENGINEERING AREA OF SPECIALIZATION;
• JUDGMENT AUTONOMY: TO BE ABLE TO PERFORM AN EFFICIENCY ANALYSIS WITH CRITICAL SPIRIT, CHOOSING THE APPROPRIATE METHOD AND CORRECTLY IMPLEMENTING IT.
• COMMUNICATION SKILLS: BEING ABLE TO COMMUNICATE THE RESULTS OF THE ANALYSIS AND ITS INFORMATION TO DIFFERENT TYPES OF INTERLOCUTORS;
• LEARNING SKILLS: TO DEVELOP THE NECESSARY SKILLS TO APPLY AND DEVELOP AUTONOMOUSLY THE METHODS LEARNED DURING THE COURSE.

Educational objectives

This course aims at addressing important strategic aspects and operational implications in the purchasing management. To this purpose, the course presents purchasing strategies of item categories, purchasing portfolio matrices and spending analysis of organizations. Then, the course describes the steps of the procurement process and examines in-depth the operational aspects of the keys underlying activities.
After completing this course, the student will master some methodological tools that will enable him to elaborate an appropriate purchasing strategy of a specific item category, to assess and select reliable and efficient providers, and to obtain terms and conditions that are responsive to the buyer firm needs.

Educational objectives

General objectives
The course combines practical sessions and exercises to introduce the main data analysis techniques (including supervised and unsupervised learning techniques) and operational tools (including R, Excel and generative AI) available for developing data analyses to support 'business activities'. Each technique presented will be accompanied by at least one case study, presented through interactive lab sessions.
More precisely, the general objectives of the course are:
• Present an overview of the role of the Data Analyst and the objectives of the possible analyses to be implemented (business purpose).
• To introduce the main software available for the implementation of the analysis techniques presented during the course.
• Present the operational use of generative AI tools for data analysis.
• Present the basic techniques for data mining and scraping and text analysis.
• Present the implementation of estimation, time series and clustering techniques.
• Provide laboratory sessions for the practical implementation of the techniques presented during the course.
• Present various applications in the field of economics and management as potential group work, to be developed by students according to their personal interests and backgrounds.
• Provide the rudiments of data presentation and data storytelling with advanced operational tools (such as shiny or powerBI-based platforms).
• To interact with students through assisted workshops, oral presentations and the realization of a project on real data.

Specific objectives
• Knowledge and understanding: demonstrate knowledge of developing data analysis techniques;
• Apply knowledge and understanding: apply specific software tools to develop data analysis techniques;
• Critical and judgment skills: be able to evaluate data sources to be used critically and independently, subsequently choosing the appropriate analysis method and implementing it correctly;
• Communication skills: be able to communicate analysis results and related information to different types of interlocutors;
• Learning ability: develop the skills necessary to independently apply and develop the various techniques learned during the course.

Educational objectives

General objectives:

Acquire the basic principles of the field of Artificial Intelligence, specifically the modeling of intelligent systems through the notion of intelligent agent.
Acquire the basic techniques developed in the field of Artificial Intelligence, concerning symbol manipulation and, more speicifically, discrete models.
Acquire the basic principles of the interaction among intelligent agents and, specifically, of the interaction between intelligent agents and humans, through natural language.

Specific objectives:

Knowledge and understanding:

Automated search in the space state: general methods, heuristic driven methods, local Search. Factored representations: constraint satisfaction problems, automated planning.
Knowledge Representation through formal systems: propositional logic, first order logic, description logic (hints), non monotonic reasoning (hints). Usage of logic as a programming language: PROLOG.
Cooperation and coordination, distributed task assignment, distributed constraint optimization, lexical, syntactic and semantic analysis of natural language.

Applying knowledge and understanding:

Modeling problems by means of the manifold representation techniques acquired through the course. Analysis of the behavior of the basic algorithms for automated reasoning.
Design and implement frameworks for multi agent interaction.

Making judgements:
Being able to evaluate the quality of a representation model for a problem and the results of the application of the reasoning algorithms when run on it.
Analyse and evaluate the key elements of the interaction among multiple agents.

Communication:
The oral communication skills are stimulated through the interaction during class, while the writing skills will be developed thorugh the analysis of exercises and answers to open questions, that are included in the final test.
The communication skills are also exercised through the presentation of a group project and its associated written report.

Lifelong learning skills:
In addition to the learning capabilities arising from the study of the theoretical models presented in the course, the problem solving capabilities of the student will be improved through the exercises where the acquired knowledge is applied.
The design and implementation of a prototype system for multi agent interaction support the learning of teamwork.

Educational objectives

KNOWLEDGE AND UNDERSTANDING.
Through the introduction of the fundamentals on the theoretical, technical and practical aspects in the design and implementation of machine learning systems for the solution of problems regarding the analysis of signals, measurements and, more generally, of big data, based on Computational Intelligence techniques such as Bayesian learning, neural networks, fuzzy logic, evolutionary algorithms, etc., the student will reinforce the knowledge acquired in the first cycle of studies. The applications in Industrial Engineering for the solution of supervised and unsupervised problems, in particular regarding optimization, approximation, regression, interpolation, prediction, filtering, pattern recognition and classification, in order to elaborate and apply orginal ideas, will be further investigated also in a research context.

CAPABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING.
Capability to analyze and solve problems related to the design, implementation and testing of machine learning algorithms, with particular reference to the development in Matlab/Python/TensorFlow environment, for developing machine learning solutions applied to problems of Industrial Engineering in the management, electrical, mechanical, logistics, biomedical fields and for the training of professional and business skills able to relate in the technical-scientific field of data analytics and business intelligence, in a context therefore broader than the field of Industrial Engineering.

MAKING AUTONOMOUS JUDGEMENTS.
The main goal of the course is to allow the student to develop machine learning systems through an appropriate formulation of the problem, a good choice of algorithms suitable for solving the problem and performing experiments in laboratory activities in order to evaluate the efficacy of the proposed solution. During the course, the main concepts and ideas that allow the effective use of machine learning algorithms in industrial applications, rather than their purely mathematical formulation, will be mainly exposed. Therefore, the student will integrate the acquired knowledge to manage the complexity of an inductive learning mechanism where new knowledge is extracted and oriented to the solution of applicatiion problems, starting from the limited information due to the organizational contingency of the course.

COMMUNICATE SKILLS.
The topics covered in the course are of general interest in the scientific and industrial fields, in particular in the analysis of materials, in the design of devices and circuits, in automation and control systems, in the inversion of physical and abstract models for decision-making processes, in the management of complex networks (smart grids, energy and freight distribution, biological and social networks, etc.). Nonetheless, applications of new technologies will be introduced in the development of innovative computing systems, primarily quantum computers, in which the use of computational intelligence and machine learning algorithms for the effective and cutting-edge exploitation of the same ones is essential. Following this course, the student will be able to communicate the knowledge acquired to specialists and non-specialists in the world of work and research, where she/he will develop the subsequent scientific and/or professional activities.

LEARNING SKILLS.
The didactic methodology implemented in the course requires an autonomous and self-managed activity of study during the development of vertical homeworks for the didactic and/or experimental investigation of some specific topics.

Educational objectives

###################
General Objectives:
###################

Major advances in technology have resulted in the widespread implementation of information systems into businesses and organizations.

This course introduces languages, principles and methods of process modeling, analysis and innovation as critical factors to the
overall success of a business.

The course centers around the role of conceptual (sometimes referred as business) process modeling as a means to understand and capture the
workflows of interest in information systems of various kind. Students will learn the elements of process models and their precise meaning
using the Business Process Model and Notation (BPMN) international standard.

The course will cover processes within organizations (process orchestrations) and also interacting processes involving several organizations
(process choreographies), and will look at techniques to analyze and improve such processes from a formal perspective.

The course will also provide a basic knowledge and understanding of how to design, test and implement information systems for executable processes.

Finally, the course will present methods and tools to properly use process mining techniques, which enable to discover process models (whose structure
is unknown at the outset) starting from the logs recording the concrete events executed by the real workflows.

####################
Specific Objectives:
####################

----------------------------
Knowledge and understanding:
----------------------------
At the end of the course, the students:
- learn the main methods to carry out a BPM (Business Process Management) project;
- are able to model a process with the BPMN standard;
- are able to implement and execute a process through a real information system;
- understand process mining algorithms and techniques.

-------------------------------------
Applying knowledge and understanding:
-------------------------------------
The students will be able to use suitable methodological and technological solutions for
(i) modeling a process in BPMN;
(ii) analysing it with quantitative techniques;
(iii) executing and monitoring it with an information system.

------------------
Making judgements:
------------------
The student acquires autonomy of judgment in proposing the most suitable approach to carry out a BPM project.

--------------
Communication:
--------------
The project activities and the lectures of the course allow the students to develop the proper abilities to communicate/share the design choices and
development methods for realizing any step of the business process life-cycle.

-------------------------
Lifelong learning skills:
-------------------------
In addition to the traditional learning skills provided by studying the teaching material, the project activities stimulate the student to
deepen her knowledge of the BPM topic, to improve the teamwork, and to the concrete application of the concepts and techniques investigated
during the course.

Educational objectives

To provide some fundamental concepts of probability and statistics and to introduce some stochastic models for finance. Trying to enable the students to refine their critical aptitudes, to render them able to face not only "routine" problems, but also any "new" matter or situation.

Educational objectives

To provide some fundamental concepts of probability and statistics and to introduce some stochastic models for finance. Trying to enable the students to refine their critical aptitudes, to render them able to face not only "routine" problems, but also any "new" matter or situation.

Educational objectives

To provide some fundamental concepts of probability and statistics and to introduce some stochastic models for finance. Trying to enable the students to refine their critical aptitudes, to render them able to face not only "routine" problems, but also any "new" matter or situation.

Educational objectives

The purpose of this course is to study mathematical models useful in taking decisions when more than a decision maker is present.
In particular variational inequalities and game theoretic models will be analyzed in detail. Emphasis will be given to computational aspects.
At the end of the course the student will be able to cast equilibrium problems as variational inequalities or by using game models and to develop suitable solution algorithms. He/She will also learn how to use game theoretic models and how to find algorithmically their equilibria and in realistic cases.

Knowledge and understanding
The aim of the course is to give students a basic knowledge of analytic methods for multi-agent environments analysis.
Students will be able to model mathematically complex interactions among (economic) agents and to analyze the consequences of different choices.

Applying knowledge and understanding
By the end of the course students will be able apply analytical tools to the analysis of economic and industrial settings.

Making judgements
Lectures and practical exercises will provide students with the ability toassess the main strengths and weaknesses of the learned theoretical models.
Students will also be able to gauge consequences of different decisionswhen using multi agent models.

Communication
By the end of the course, students will be able to discuss relevant information, ideas, problems and solutions both with a specialized and a non-specialized audience.

Lifelong learning skills
Students are expected to develop those learning skills necessary to undertake additional studieson the relevant topics with a high degree of autonomy. During the course, students are encouraged to investigate further topics of major interest by consulting supplementary academic publications, specialized books, and internet sites.

Educational objectives

1) Knowledge and understanding
During the lessons of Data-driven Economics, students acquire the basic theoretical elements of econometric analysis. Theoretical lessons are aimed at guiding students in the acquisition of the basics of simple and multiple regression models, starting from the relative assumptions, and then proceeding with the estimation and inference procedures. The course contents cover both the estimation of linear and non-linear models and the analysis of both cross-sectional and longitudinal data.
2) Applicate applying knowledge and understanding
The students of the Data-driven Economics course are able to apply the notions acquired during the theoretical lessons to a wide range of problems of an empirical nature. They acquire the ability to build econometric models aimed at giving empirical content to economic relations and are also able to establish a causal link between two or more variables in the economic field.
3) Making judgements
Students are encouraged to critically discuss empirical studies published in the economic/managerial field in the classroom. The Data-driven Economics course also includes a laboratory in which students apply the acquired knowledge of econometrics to the estimation of empirical models carried out using data made available by the teacher.
4) Communication skills
At the end of the course, students are able to illustrate and explain the strengths and weaknesses of a wide range of empirical methodologies to a variety of heterogeneous interlocutors in terms of training and professional role. The acquisition of these skills is verified and evaluated not only during the final exam, by means of a written test and a possible oral test, but also during flipped class sessions in which, individually or in groups, students are called to present empirical studies published in the economic/managerial field.
5) Learning skills
Students acquire the ability to independently conduct empirical analyses by building econometric models to be estimated using data with diversified structures. The tools provided by the course allow for the analysis of systems in which a large number of factors simultaneously contribute to explaining their states and impact assessments that take into account the uncertainty and risk inherent in the application of policies. The acquisition of these skills is verified and evaluated on during the final exam, by means a written test and a possible oral test, in which the student can be called to discuss empirical problems on the basis of the topics covered and the reference material distributed during the course.

Educational objectives

ENG
GENERAL OBJECTIVES
The course aims to provide students with a fundamental understanding of concepts and tools relevant to marketing. Specifically, the course aims to help students understand: the main forces of the marketing environment; the marketing information system; consumer and business buying behaviors; the stages and tools for formulating and implementing a marketing strategy. Furthermore, through the analysis of a series of case studies, the course aims to develop students' critical analysis skills, enabling them to interpret and explain business behavior and outcomes within marketing strategies in light of the concepts learned during the course.

SPECIFIC OBJECTIVES
KNOWLEDGE AND UNDERSTANDING. The course will enable students to acquire knowledge and understanding of the main concepts and fundamental tools of Marketing. Students will learn to recognize and master best practices and success factors of Marketing and apply them in real-world contexts.

APPLICATIVE SKILLS. Thanks to the course, students will be able to formulate a marketing plan, as well as critically evaluate marketing strategies.

JUDGMENT AUTONOMY. The course will empower students to choose, given the main environmental forces, the characteristics of the enterprise and innovation, the best marketing strategies. Additionally, students will develop the ability to critically analyze marketing.

COMMUNICATION SKILLS. By the end of the course, students will be able to explain marketing concepts using internationally established terminology and models, organize information and data in a format and reporting process understandable to professionals.

LEARNING ABILITY. Students will develop independent study skills and critical understanding and evaluation of marketing strategies and related tools.

Educational objectives

GENERAL OBJECTIVES
The course aims to provide students with a basic understanding of concepts and tools relevant to Innovation Management. Specifically, the course aims to help students understand: the forms, models, and sources of innovation; standard conflicts and the definition of dominant design; market entry timing choices; innovation protection mechanisms; the process of developing a new product; the integration of environmental sustainability into marketing strategy and new product development. Furthermore, through the analysis of a series of case studies, the course aims to develop students' critical analysis skills, enabling them to interpret and explain business behavior and outcomes within the context of technological innovation strategies in light of the concepts learned during the course.

SPECIFIC OBJECTIVES
KNOWLEDGE AND UNDERSTANDING. The course will enable students to acquire knowledge and understanding of the main concepts and fundamental tools of Innovation Management. Students will learn to recognize and master best practices and success factors of Innovation Management and apply them in real-world contexts.

APPLICATIVE SKILLS. Thanks to the course, students will be able to critically evaluate an enterprise's technological innovation strategies, as well as classify products based on their environmental impact.

JUDGMENT AUTONOMY. The course will empower students to choose, given the main environmental forces, the characteristics of the enterprise and innovation, the best technological innovation strategies. Additionally, students will develop the ability to critically analyze innovation management.

COMMUNICATION SKILLS. By the end of the course, students will be able to illustrate concepts of innovation management using internationally established terminology and models, organize information and data in a format and reporting process understandable to professionals.

LEARNING ABILITY. Students will develop independent study skills and critical understanding and evaluation of marketing and technological innovation strategies and related tools

Educational objectives

Knowledge and understanding
The course introduces students to the economics and management of networks. On the one hand, the course illustrates the main features of the new information economy, and discusses the prevailing and emerging business models. On the other hand, it explores competition and regulation issues in liberalized network industries, such as telecommunications, energy, and transportation.

Applying knowledge and understanding
Students are expected to be able to use methods and models of microeconomics and industrial organization to understand and analyze the impact of technology and demand on market structure, firms’ strategies and business models in the new information economy. They will also gain insight on the rationale and the scope for public policy in network industries.

Making judgements
Lectures, practical exercises and problem-solving sessions will provide students with the ability to assess the main strengths and weaknesses of theoretical models when used to explain empirical evidence and case studies in the new information economy and in network industries.

Communication
By the end of the course, students are able to point out the main features of the new information economy and network industries, and to discuss relevant information, ideas, problems and solutions both with a specialized and a non-specialized audience. These capabilities are tested and evaluated in the final written exam and possibly in the oral exam as well as in the project work.

Lifelong learning skills
Students are expected to develop those learning skills necessary to undertake additional studies on relevant topics in the field of the new information economy and network industries with a high degree of autonomy. During the course, students are encouraged to investigate further any topics of major interest, by consulting supplementary academic publications, specialized books, and internet sites. These capabilities are tested and evaluated in the final written exam and possibly in the oral exam as well as in the project work, where students may have to discuss and solve some new problems based on the topics and material covered in class.

Educational objectives

Devising new machine learning methods and statistical models is a fun and extremely fruitful “art”. But these powerful tools are not useful unless we understand when they work, and when they fail. The main goal of statistical learning theory is thus to study, in a
statistical framework, the properties of learning algorithms mainly in the form of so-called error bounds.
This course introduces the techniques that are used to obtain such results, combining methodology with theoretical foundations and computational aspects. It treats both the basic principles to design successful learning algorithms and the “science” of analyzing an algorithm’s statistical properties and performance guarantees.
Theorems are presented together with practical aspects of methodology and intuition to help students develop tools for selecting appropriate methods and approaches to problems in their own data analyses.
Methods for a wide variety of applied problems will be explored and implemented on open-source software like R (www.r-project.org), Keras (https://keras.io/) and TensorFlow (https://www.tensorflow.org/).
Knowledge and understanding

On successful completion of this course, students will:
know the main learning methodologies and paradigms with their strengths and weakness;
be able to identify a proper learning model for a given problem;
assess the empirical and theoretical performance of different learning models;
know the main platforms, programming languages and solutions to develop effective implementations.

Applying knowledge and understanding

Besides the understanding of theoretical aspects, thanks to applied homeworks and a final project possibly linked to hackathons or other data analysis competitions, the students will constantly be challenged to use and evaluate modern learning techniques and algorithms.

Making judgements

On successful completion of this course, students will develop a positive critical attitude towards the empirical and theoretical evaluation of statistical learning paradigms and techniques.

Communication skills

In preparing the report and oral presentation for the final project, students will learn how to effectively communicate original ideas, experimental results and the principles behind advanced data analytic techniques in written and oral form. They will also understand how to offer constructive critiques on the presentations of their peers.

Learning skills

In this course the students will develop the skills necessary for a successful understanding as well as development of new learning methodologies together with their effective implementation. The goal is of course to grow a active attitude towards continued learning throughout a professional career.

Educational objectives

ENG
GENERAL OBJECTIVES
The course aims to provide students with a fundamental understanding of concepts and tools relevant to marketing. Specifically, the course aims to help students understand: the main forces of the marketing environment; the marketing information system; consumer and business buying behaviors; the stages and tools for formulating and implementing a marketing strategy. Furthermore, through the analysis of a series of case studies, the course aims to develop students' critical analysis skills, enabling them to interpret and explain business behavior and outcomes within marketing strategies in light of the concepts learned during the course.

SPECIFIC OBJECTIVES
KNOWLEDGE AND UNDERSTANDING. The course will enable students to acquire knowledge and understanding of the main concepts and fundamental tools of Marketing. Students will learn to recognize and master best practices and success factors of Marketing and apply them in real-world contexts.

APPLICATIVE SKILLS. Thanks to the course, students will be able to formulate a marketing plan, as well as critically evaluate marketing strategies.

JUDGMENT AUTONOMY. The course will empower students to choose, given the main environmental forces, the characteristics of the enterprise and innovation, the best marketing strategies. Additionally, students will develop the ability to critically analyze marketing.

COMMUNICATION SKILLS. By the end of the course, students will be able to explain marketing concepts using internationally established terminology and models, organize information and data in a format and reporting process understandable to professionals.

LEARNING ABILITY. Students will develop independent study skills and critical understanding and evaluation of marketing strategies and related tools.

Educational objectives

General outcomes:

The course will present a broad survey of topics at the interface of computer
science, data science, and economics, emphasizing efficiency, robustness, and application to emerging online markets. It will introduce the principles of algorithmic game theory and mechanism design, algorithmic market design, as well as machine learning in games and markets. It will demonstrate applications to case studies in Web search and advertising, network economics, Data, cryptocurrency, and AI markets.

Specific outcomes:
Knowledge and understanding:
The algorithmic and mathematical economics principles underlying the design and the operation of efficient and robust online markets. The application of these principles in concrete examples of online markets.

Applying knowledge and understanding:
Being able to design and analyze algorithms for concrete online market applications with respect to the requirements of efficiency and robustness.

Making judgements:
Being able to evaluate the quality of an algorithm for online market applications, discriminating the modeling aspects from those related to algorithmic and system implementation.

Communication skills:
Ability to communicate and share the modeling choices and system requirements, as well as the results of the analysis of the efficiency of online market algorithms.

Learning skills:
The course stimulates the students to acquire learning skills at the crossroads of computer science, economics, and digital market applications, including the different languages used in these fields.

Educational objectives

GENERAL OBJECTIVES
The course aims to provide students with a basic understanding of concepts and tools relevant to Innovation Management. Specifically, the course aims to help students understand: the forms, models, and sources of innovation; standard conflicts and the definition of dominant design; market entry timing choices; innovation protection mechanisms; the process of developing a new product; the integration of environmental sustainability into marketing strategy and new product development. Furthermore, through the analysis of a series of case studies, the course aims to develop students' critical analysis skills, enabling them to interpret and explain business behavior and outcomes within the context of technological innovation strategies in light of the concepts learned during the course.

SPECIFIC OBJECTIVES
KNOWLEDGE AND UNDERSTANDING. The course will enable students to acquire knowledge and understanding of the main concepts and fundamental tools of Innovation Management. Students will learn to recognize and master best practices and success factors of Innovation Management and apply them in real-world contexts.

APPLICATIVE SKILLS. Thanks to the course, students will be able to critically evaluate an enterprise's technological innovation strategies, as well as classify products based on their environmental impact.

JUDGMENT AUTONOMY. The course will empower students to choose, given the main environmental forces, the characteristics of the enterprise and innovation, the best technological innovation strategies. Additionally, students will develop the ability to critically analyze innovation management.

COMMUNICATION SKILLS. By the end of the course, students will be able to illustrate concepts of innovation management using internationally established terminology and models, organize information and data in a format and reporting process understandable to professionals.

LEARNING ABILITY. Students will develop independent study skills and critical understanding and evaluation of marketing and technological innovation strategies and related tools

Educational objectives

Student must will able to:
- choose an additive manufacturing technology in order to comply with product specifications
- apply the Design for Additive Manufacturing
- analyze a CNC code
- employ a Computer Aided Manufacturing
- plan a Flexible Manufacturing System and a Flexible Assembly System

Educational objectives

General Objectives of the course

The course, with an interdisciplinary approach, combines theoretical lectures on the economics of production, with lectures on the main econometric approaches proposed in the literature, including recent developments, and practical sessions to introduce to the main open source software available to carry out productivity and efficiency analysis.
The main objectives of the course are:
- Present a general overview on the economic theory of productivity and efficiency;
- Propose a unified framework on the main methodologies available to estimate and compare productivity and efficiency of Decision Making Units (DMUs);
- Make an introduction to the main open source software available to estimate productivity and efficiency;
- Provide laboratory sessions to implement productivity and efficiency analyses in practice;
- Provide the basic concepts to analyse the specialised literature;
- Interact with students through assisted laboratory and the realization of a practical work on real data, seminars and oral presentations.

Specific Objectives
• KNOWLEDGE AND UNDERSTANDING: DEMONSTRATE THE KNOWLEDGE OF THE BASIC ELEMENTS OF PRODUCTIVITY AND EFFICIENCY ANALYSIS;
• ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING: TO BE ABLE TO APPLY EFFICIENCY ANALYSIS TECHNIQUES LEARNED DURING THE COURSE IN ITS OWN ENGINEERING AREA OF SPECIALIZATION;
• JUDGMENT AUTONOMY: TO BE ABLE TO PERFORM AN EFFICIENCY ANALYSIS WITH CRITICAL SPIRIT, CHOOSING THE APPROPRIATE METHOD AND CORRECTLY IMPLEMENTING IT.
• COMMUNICATION SKILLS: BEING ABLE TO COMMUNICATE THE RESULTS OF THE ANALYSIS AND ITS INFORMATION TO DIFFERENT TYPES OF INTERLOCUTORS;
• LEARNING SKILLS: TO DEVELOP THE NECESSARY SKILLS TO APPLY AND DEVELOP AUTONOMOUSLY THE METHODS LEARNED DURING THE COURSE.

Educational objectives

The course gives on-field experience of Operations Management, from an operational and technical point of view. The course develops one of the main topics of Operations Management, e.g. company-market relations, supply chain management, production and inventory management.

EXPECTED LEARNING OUTCOMES. Knowledge and understanding: Deepening and consolidation of the knowledge provided in the Operations Management course. Capability: Expected learning outcomes include the ability to develop analyses, model problems, and identify the best techniques for solving major characteristic problems in production management, materials management, logistics management, and supply chain management through project work and on-field experience.

Educational objectives

The course aims to describe the founding principles, the scope and the fundamental toolsand
methodologies of project management and of organizational processes.
Starting from the concept of integrated management of projects, all the
main methods for managing the performance variables of quality, time and
cost will be proposed. In line with the main standard processes of
project management the internationally standardized project management
terminology will be used. The course also intends to present the
principles and techniques of business process re-engineering and
management.Risultati di apprendimento attesi (Inglese):At the
end of the course the student will be able to plan a project starting
from the objectives of quality, time and cost defined by internal or
external customers of a company. She/he will also be able to critically
analyze an ongoing project proposing both organizational and managerial
improvements and both the use of correct project management
methodologies.

Educational objectives

The course aims at deepening the design, the implementation, the execution and the analysis of the results of
discrete event simulation models. Particular focus will be on the use of specialized software packages and languages
for discrete event simulation and their possible use in connection with optimization software. Students will be
directly involved in laboratory activities and in particular in the implementation of real case studies.

Knowledge and understanding:
Techniques for implementing a discrete event simulation model. Use of software packages dedicated to
discrete event simulation and their possible integration with optimization software.

Applying knowledge and understanding:
To be able to carry out a complete study of a real problem through discrete event simulation, from the preliminary analysis
of the processes, the implementation, up to the interpretation of the results.

Making judgements:
Knowing how to identify the fundamental characteristics of a real process for the construction of a model of
discrete event simulation. Knowing how to evaluate the impact of the output of a simulation on the real case in analysis.

Communication skills:
The laboratory activities will allow the student to learn communicating and sharing simulation models and their outputs.

Learning skills:
The laboratory activities will stimulate the students to the autonomous realization of simulation models, to teamwork,
and to the concrete application of the techniques learned in the course.

Educational objectives

Main course’s objective is
developing digital competences to make citizens able to use Information
and Communication Technologies (ICT) at work, in day-to-day relationships, in
dealing with public services as well as in culture, entertainment, leisure and
when participating in community and political dialogues. This course contributes
to actualize the EU i2010 program “increasing social
inclusion through reducing digital divide to build a society for
all”. The course promotes ICT use also to put in action the Italian Digital
Administration Low as well as the ICT right use (art.3) and the Public
Administration Data Availability (art 50 capo V).

Educational objectives

The objective is to provide the management engineer with the basis for understanding the theory and principles of innovative optical, photothermal, photoacoustic, radiometric and thermographic techniques and instruments, and to understand the main applications together with their industrial relapses and with a deep analysis of the economical impacts and parameters.

The topics are organized to provide scientific technical expertise in order to work in the field of applied research, making easier the employment of the new engineer in industry.

Contents of the proposed course:

The course will provide the theoretical bases of the optical systems, the laser with its applications. Photothermal, photoacoustic, radiometric, and infrared techniques will be introduced for nonsdestructive evaluation and testing of materials, together with the many applications in different fields: industry, environment, energy, but also biology, medicine, and in the emerging sector of agri-food. Final comparisons will be introduced among the diagnostic techniques by using parameters of the management engeneering. The course contains also some experimental activities in laboratory and the data analysis and processing.

Educational objectives

The specific aim is to allow the student to use and expand the bulk of knowledge acquired during the course of study performing some activities in an industrial setting, a company, or a research laboratory.