Master in Computer Science and Software Engineering

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Master in Computer Science and Software Engineering

The SIT program is flexible and adapted to many different individual situations. It is available both onsite in Schaffhausen and in an online offering, as well as any onsite-online combination. It offers qualified students attractive scholarships and the possibility of a second year in one of our partner universities in Europe, the USA, and Asia.

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Program overview

At SIT, students can choose between three different program options - the classic 2-year program, double track with world-leading universities, and the fast track.

Classic program

MSc in Computer Science and Software Engineering

Duration: 4 semesters, 120 ECTS

Study plan by terms

FALL 2021 (30 ECTS)

Technical skills
- Quality Engineering (6 ECTS)
- Software Construction, Software Architecture, and Software Engineering (6 ECTS)
- Cyber Protection (6 ECTS)

Management skills
- Product Vision, Product Strategy, Innovation, and Marketing (6 ECTS)

Leadership skills
- Organizational Behavior and Industrial-Organizational Psychology (3 ECTS)

Capstone Project: geographically distributed teams working on industrially relevant projects in cooperation with companies with academic advisors or develop a commercialization project at the local tech park facilities (3 ECTS).

SPRING 2022 (30 ECTS)

Technical skills
Data Science (6 ECTS)
Architectural Strategy (6 ECTS)
Dynamic Analysis and Deep Learning (6 ECTS)

Management skills
Product Design, Portfolio Management and Analytics (6 ECTS)

Leadership skills
Agile Leadership and Strategic Management (3 ECTS)

Capstone Project: geographically distributed teams working on Industrially relevant projects in cooperation with companies with academic advisors or develop a commercialization project at the local tech park facilities (3 ECTS)

SUMMER 2022

Elective Internship
The master offers internships within SIT research laboratories and within Swiss and international companies, thanks to the SIT close partnership with well-known industry partners.

Internships give you the opportunity to improve your experience with international research projects and leading industrial projects, both extremely important for employment after your studies.

FALL 2022 (30 ECTS)

Technical skills
System Protection (6 ECTS)
- Programmatic Marketing (3 ECTS)
Quantum Informatics (3 ECTS)

Management skills
Transformational Change Management (6 ECTS)

Leadership skills
Customer-centric Mindset and Agile Delivery Management (3 ECTS)
Entrepreneurship & Intrapreneurship (3 ECTS)

Capstone Project: geographically distributed teams working on Industrially relevant projects in cooperation with companies with academic advisors or develop a commercialization project at the local tech park facilities (6 ECTS)

SPRING 2023 (30 ECTS)

Master Thesis

Double-degree program

MSc in Computer Science and Software Engineering and master's degree in a partner university. Admission to the double-degree program is limited. Full scholarships are available.

At the moment, SIT offers a double-degree program with the following partner universities: 
- Carnegie Mellon University, CMU (Pittsburgh USA)
- National University of Singapore, NUS (Singapore)

English is the official language of the double-degree programs.

Duration: 4 semesters, 2 summers, 140 ECTS

Double degree programs students must:
- be admitted to the MSc in CS-SE,
- be admitted to the program of the partner institution according to the bilateral agreements.

Study plan by terms

FALL 2021 (30 ECTS)

Technical skills
Quality Engineering (6 ECTS)
Data Science (6 ECTS)
Cyber Protection (6 ECTS)

Management skillsProduct Vision, Strategy, Innovation and Marketing (6 ECTS)

Leadership skills
- Human and Social Psychology (3 ECTS)

Capstone Project: geographically distributed teams working on Industrially relevant projects in cooperation with companies with academic advisors or develop a commercialization project at the local tech park facilities (3 ECTS)

SPRING 2022 (30 ECTS)

Technical skills
Data Science (6 ECTS)
Architectural Strategy (6 ECTS)
Dynamic Analysis and Deep Learning (6 ECTS)

Management skills
Product Design, Portfolio Management, and Analytics (6 ECTS)

Leadership skills
Agile Leadership and Strategic Management (3 ECTS)

Capstone Project: geographically distributed teams working on Industrially relevant projects in cooperation with companies with academic advisors or develop a commercialization project at the local tech park facilities (3 ECTS)

FALL 2022 (30 ECTS)

Semester at the partner university:
- Carnegie Mellon University, CMU (full scholarships available)
- National University of Singapore, NUS (full scholarships available)

SPRING 2023 (30 ECTS)

Semester at the partner university:
- Carnegie Mellon University, CMU (full scholarships available)
- National University of Singapore, NUS (full scholarships available)

SUMMER 2023 (20 ECTS)

Master Thesis (20 ECTS)

Fast track

MSc in Computer Science and Software Engineering
Duration: 120 ECTS in 3 semesters and summer

Fast track program students must:
- be admitted to the MSc in CS-SE with no education debt,
- pass an interview with the master admission committee.

FALL 2021 (30 ECTS)

Technical skills
Quality Engineering (6 ECTS)
Software Construction, Software Architecture, and Software Engineering (6 ECTS)
Cyber Protection (6 ECTS)

Management skills
Product Vision, Product Strategy, Innovation and Marketing (6 ECTS)

Leadership skills
Organizational Behavior and Industrial-Organizational Psychology (3 ECTS)

Capstone Project: geographically distributed teams working on Industrially relevant projects in cooperation with companies with academic advisors or develop a commercialization project at the local tech park facilities (3 ECTS).

SPRING 2022 (36 ECTS)

Technical skills
Data Science (6 ECTS)
Architectural Strategy (6 ECTS)
Dynamic Analysis and Deep Learning (6 ECTS)

Management skills
Product Design, Portfolio Management, and Analytics (6 ECTS)

Leadership skills
Agile Leadership and Strategic Management (3 ECTS)

Master Thesis (6 ECTS)
Thesis to be carried on as extra time in the second and third semesters and full time during the summer break.

Capstone Project: geographically distributed teams working on Industrially relevant projects in cooperation with companies with academic advisors or develop a commercialization project at the local tech park facilities (3 ECTS).

SUMMER 2022 (18 ECTS)

Master Thesis (18 ECTS)
Thesis to be carried on as extra time in the second and third semesters and full time during the summer break.

FALL 2022 (36 ECTS)

Technical skills
System Protection (6 ECTS)
- Programmatic Marketing (3 ECTS)
Quantum Informatics (3 ECTS)

Management skills
Transformational Change Management (6 ECTS)

Leadership skills
Customer-centric Mindset and Agile Delivery Management (3 ECTS)
Entrepreneurship & Intrapreneurship (3 ECTS)

Master Thesis (6 ECTS)
Thesis to be carried on as extra time in the second and third semesters and full time during the summer break.

Capstone Project: geographically distributed teams working on Industrially relevant projects in cooperation with companies with academic advisors or develop a commercialization project at the local tech park facilities (6 ECTS).

Flexible and adaptable teaching style

The unique agile flip blended eLearning formula combines lectures in the classroom, live broadcasts for online interactive participation and recorded lectures, lab activities in agile geographically distributed teams under the supervision of expert teaching assistants, individual and team study.

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Agile flip blended eLearning

The unique agile flip blended eLearning formula combines lectures in the classroom, live broadcasts for online interactive participation and recorded lectures, lab activities in agile geographically distributed teams under the supervision of expert teaching assistant, individual and team study

  • Access to world-class scientists and educators
    The SIT master in Computer Science and Software Engineering benefits from the support of a unique team of worldwide leaders. 
  • Entrepreneurial feeling and can-do mentality
    Familiarity with industrial-scale applications, business, and people is essential both for technology leaders.
  • A program both deep and broad for technology leaders
    Deep technical interdisciplinary knowledge is the cornerstone for technology leaders. 
  • Strong liaisons with industry
    Proximity to top industries is a unique opportunity to seamlessly entering both industrial and academic careers.
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Personalized participation program

The SIT agile eLearning formula allows students to personalize the participation levels from a full residential study to online participation with quarterly visits to the SIT campus

  • High-tech & high-touch study environment
    Contemporary learning is a complex and fascinating activity that cannot be confined to classwork.
  • Student scholarship
    Learning is a unique opportunity for all talented people.

Facts and figures

Academic degree

Master of Science in Computer Science and Software Engineering (MSc CS-SE)

Program start

September 13, 2021

Instruction language

Teaching language of the program is English

Application deadline

August 31, 2021 - for all applicants

Study duration
  • Classic program (120 ECTS): Sep 2021 - Jun 2023 
  • Fast track (120 ECTS): Sep 2021 - Feb 2023 
  • Double degree (140 ECTS): Sep 2021 - Sep 2023

Study mode: full-time 

Tuition fee
  • 5,000 CHF per semester for non-Swiss residents.
  • 2,500 CHF per semester for Swiss residents.

Note: we provide scholarships

Career opportunities and industrial partners

Chief Architect (CA)

A crucial and active horizontal role to drive the technology delivery roadmap across the organization. 

Chief Product Officer (CPO)

A strategic leader, visionary, and team supervisor of new-generation product management in which computer science, business, and innovation are combined.

Chief Program Officer (CPgmO)

A new leader who focuses on program value flow and delivery, stakeholder communication, cadence & planning, inter-team collaboration, and continuous improvement.

Chief Development Officer (CDO)

A strategic leader who shapes an enabling engineering environment – people, structure, agile processes, and tools.

Chief Security Officer (CSO)

A transformational leader who takes a "bodyguard" rather than a "gate-keeper" approach.

Chief officers shall be familiar with:

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Deep technical skills based on real-world applications
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Management skills to supervise large-scale technology projects
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Adaptability to the changing technology landscape

It's not our assumption, CEOs have told us about these important qualities to have at graduation. Over 30 CEOs and CTOs of tech companies were interviewed to secure the success of the SIT Master program.

SIT and its syllabus has been specifically developed to tackle current challenges in industry, including the shortage of future leaders joining the software sector.

— Serguei Beloussov, CEO in Acronis

To ensure our students leave SIT as highly employable and sought-after technologists, we use our long-established technology network all over the globe to give our students access to the industry-led teaching and real-world problem solving. Our connections with the industry proved incredibly valuable when the course curriculum was at the planning stage, as it meant world-leading business owners could have a say in the skills taught as part of the Master's course.

The newly developed MSc CS-SE at SIT provides the next generation of technical leaders with the skills they need to accelerate research and innovation in the fields of emerging computer science technologies.

We are proud of our curriculum, as there's nothing quite like it. This scientifically impeccable course is entirely up to date with what the industry needs. Our industrial partners offer great opportunities for summer internships and future jobs.

Our industry partners

  • Acronis is a leader in cyber protection
  • Acumatica is a leading innovator in cloud ERP
  • Parallels is a global leader in cross-platform solutions
  • Plesk is a leading WebOps hosting platform
  • cPanel is an industry-leading hosting platform
  • Runa capital is a global venture capital firm built by serial entrepreneurs

Apply for the Master's degree at SIT

Become a technical leader. Get your MSc in Computer Science and Software Engineering from SIT.

SIT STAR scholarship

SIT offers a wide range of scholarships in cooperation with partner companies to support talented students in their education and future career.

We offer:

  • I chose SIT as my career plan was to move from a software engineering role to that of a product manager. Among the best tech MBA programs, CMU's MSPM is a unique collaboration between the School of Computer Science and Tepper School of Business. SIT has built the joint program with CMU, providing required financial support and guidance from industry experts. It has laid the foundation of my career in the field of product management.

    Arpita Ghosh, Product Management Student at SIT

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Quality Engineering

Specific semester: 1st 

Number of credits: 6 ECTS 

Instructor: Mauro Pezzè

Software quality can be defined as the degree of satisfaction of the requirements; it represents an essential part of the software development and cannot be guaranteed apriori, but must be verified both during and after the development. 

This course introduces the main testing and analysis techniques that can be used to identify failures and verify the quality of software systems. 

The course introduces the general testing and analysis principles and the basic techniques, shows how to apply them to solve relevant quality problems, illustrates complementarities and differences among the different techniques, and presents the organization of a coherent quality process. 

The course provides the elements needed to understand principles, techniques and processes that comprise the basic background of test designer, quality manager and project manager. 

At the end of the course, the students will be able to define and implement quality plans for complex software systems. The student will have the basic knowledge of a project and a quality manager. 

Overall objective 

Estimating and planning system quality. 

Detailed objectives 

  • Understanding the dimensions of software and system quality
  • Learning the core techniques underlying quality assurance
  • Learning techniques and approaches to cope with functional and non-functional quality
  • Organizing an agile and effective quality process.

 
Course summary 

  • Quality dimensions, a general framework, basic principles
  • Dependence and data flow models and testing
  • Dynamic symbolic execution
  • Finite-state verification and model checking
  • Test case selection and adequacy criteria
  • Fault-based testing and mutation analysis
  • Combinatorial testing
  • Code inspection and review
  • Testing concurrent and distributed systems
  • Fuzz and security testing
  • Usability testing
  • Agile quality planning
  • Test automation
  • TDD (test-driven development)
  • Regression testing and maintenance

 
Prerequisite knowledge 

  • (required) Programming skills in an imperative language at CS bachelor level
  • (required) Algorithms and data structure at CS bachelor level
  • (required) Basic skills in software testing: structural testing, Junit
  • (optional) Basic knowledge of software engineering and IDEs at CS bachelor level
  • (optional) Discrete math at CS bachelor level
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Software Construction

Specific semester: 1st 
Number of credits: 6 ECTS 
InstructorProf. Dr. Bertrand Meyer 

Data analytics and big data are key enabling technologies for modern society. Managing the enormous amount of data available in almost every application domain is becoming a necessity. 

The course presents the core technologies to analyze big data. It presents approaches to mine, manage and visualize structured and unstructured data. It introduces the core data analytics technologies and their combination with machine learning to analyze big data. It presents the application of data analytics and big data in the context of system monitoring and evolution, society and financial analysis and prediction. 

Overall objective 
Analyzing and processing big and streaming data to infer system properties and evolution. 

Detailed objectives 

  • Understanding data analytics and its applications
  • Mining and searching unstructured data
  • Managing and visualizing big and streaming data
  • Application of data analytics with emphasis on system monitoring, society and finance


Course summary 

  • Data management and visualization
  • Machine learning and decision models
  • Statistical methodology for big data
  • Streaming data management and time series analysis
  • Text mining and search
  • Social media analytics
  • Fintech and biz intelligence
  • Applications


Prerequisite knowledge 

  • (required) Basics of static and probabilistic analysis at CS bachelor level
  • (required) Discrete math at CS bachelor level
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Cyber Protection

Specific semester: 1st 
Number of credits: 6 ECTS
InstructorAlessandra Gorla

System security is a key issue for modern society. Designing and verifying secure software systems is a cornerstone of system security. 

The course provides the elements needed to understand and master the core technology to engineer and verify secure software systems. It will introduce the main approaches to engineer secure systems. It will present the main approaches to test and verify the security of software systems. It will discuss security issues for security critical systems and well as common software systems. It will present how to organize security engineering within popular software development processes. 

Overall objective 
Designing, verifying, and maintaining secure software systems. 

Detailed objectives 

  • Understanding software security in the context of system security 
  • Learning how to engineer secure software systems 
  • Managing security within the software development process 
  • Learning techniques and tools to test and verify security aspects 

Course summary 

  • Software security in the context of system security 
  • Security engineering 
  • Formal methods for information security 
  • Fuzz testing and verification of security aspects 
  • Program Analysis for System Security + Reliability 
  • Formal Methods for Information Security 
  • Online security protection 

Prerequisite knowledge 

  • (required) Programming skills at CS bachelor level 
  • (required) Algorithms and data structure at CS bachelor level 
  • (required) Basics of static and probabilistic analysis at CS bachelor level 
  • (required) Discrete math at CS bachelor level
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Software Engineering

Specific semester: 2nd
Number of credits: 6 ECTS 
InstructorBertrand Meyer

Software engineering is the body of concepts and techniques that make it possible to construct industrial software systems of high quality. The size, complexity, and ambition of systems being developed today require a systematic approach based on best practices learned over the past decades. 

Software engineering includes many aspects, both technical (requirements, design, programming, testing and other validation techniques, maintenance) and managerial (project management, metrics, empirical studies, agile methods, lifecycle models, quality assurance). 

After taking the course, students will understand the issues and challenges of successful software system construction and will be ready to apply them to build high-quality software, including in management roles. 

Course summary 

  1. Overview 
    • Nature and challenges of software development 
    • History of software construction and software engineering 
    • Overview of main issues and areas of modern software engineering 
       
  2. Software tasks and their distribution 
    • Main tasks of software construction 
    • Lifecycle models 
    • Agile development, techniques, and critical analysis 
    • Software project management 
       
  3. Specification and design 
    • Main requirements techniques 
    • Main design techniques 
    • Modeling techniques and tools 
       
  4. Techniques and tools of software engineering 
    • Configuration management
    • Testing
    • Bug tracking 
    • Team management 
    • System modeling 
       
  5. Ensuring software quality 
    • Techniques of software verification 
    • Introduction to formal methods 

Prerequisite knowledge 

  • Some programming experience. 
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Capstone Project

Specific semester: 1st, 2nd, 3rd (classic and fast tracks); 1st and 2nd (double degree program)
Number of credits: 2 ECTS (classic and fast tracks); 6 ECTS (double degree program)
Instructor: Prof. Manuel Oriol

Engineering industrially relevant systems presuppose the ability to blend technical, management, and leadership skills into a coherent process to efficiently engineer reliable systems that meet producers' and customers' needs. 

The Capstone Project provides students the opportunity to apply concepts learned in the master's in a real-life project through a-posteriori analysis, transformational adaptation, and coherent planning. 

The course spans three semesters, during which students will develop solutions for projects provided by industrial partners and SIT laboratories, who act as customers. The project is organized in agile teams working under the guidance of the instructors and the assistants. The teams will be geographically distributed and work in an up-to-date environment supported with open source IDEs and engineering tools. 

Lectures will address topics such as best practices, and interim goals. Students will meet periodically with the instructor and teaching assistants to monitor their progress towards the overall goal. 

Overall objective 
Learning how to apply the expertise acquired during the master's to engineer industrially relevant systems. 

Detailed objectives 

  • Practical experience in agile development and strategy 
  • Practical experience in agile (geographically distributed) development 
  • The ability to engineer complete solutions for an industrially relevant problem 
  • Practical experience in adaptive transformation management 

Course summary 

  • IDEs and tool support for efficient development processes 
  • Agile process management 
  • Risk management and customers centric organization 
  • Incremental development and delivery 
  • Guidelines and support for system maintenance in operation 
  • Emergency management 

Prerequisite knowledge 

  • (required) Programming skills in an imperative language at CS bachelor level 
  • (required) Algorithms and data structure at CS bachelor level
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Data Science

Specific semester: 2nd
Number of credits: 6 ECTS
Instructor: Nitin Kumar

Learning objectives

Overall objective

  • Analyzing and processing big and streaming data to infer system properties and evolution

Detailed objectives

  • Understanding data analytics and its applications 
  • Mining and searching unstructured data 
  • Managing and visualizing big and streaming data 
  • Application of data analytics with an emphasis on system monitoring, society, and finance

Data analytics and big data are key enabling technologies for modern society.

Course summary (mini-syllabus) 

  • Data management and visualization 
  • Machine learning and decision models 
  • Statistical methodology for big data 
  • Streaming Algorithms 
  • Sampling and Filtering 
  • Estimating Frequency Moments 
  • Stream Clustering 
  • NoSQL Systems 
  • Google File System 
  • Hadoop Distributed File System 
  • MapReduce 
  • Strategies to Reduce Costs 
  • Applications to Fintech and biz intelligence

Data analytics and big data are key enabling technologies for modern society.  Managing the enormous amount of data available in almost every application domain is becoming a necessity.

The course presents the core technologies to analyze big data.  It presents approaches to mine, manage and visualize structured and unstructured data.  It introduces the core data analytics technologies and their combination with machine learning to analyze big data. It presents the application of data analytics and big data in the context of system monitoring and evolution, society and financial analysis and prediction.

Prerequisite knowledge, prerequisite SIT courses if any

  • (required) Basics of static and probabilistic analysis at CS bachelor level
  • (required) Discrete math at CS bachelor level
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Architectural Strategy

Specific semester: 2nd
Number of credits: 6 ECTS 
InstructorAlessio Gambi, TA Pietro Braione

"Architectural Strategy" focuses on Software Architectures, the key element for systematically developing large and complex software systems. During the course, we study how to design, recover, analyze, and document Software Architectures and understand how the main design decisions comprising them influence the quality attributes of the resulting systems.

Objectives and learning outcomes

Overall objective:

Designing, engineering and managing complex architectures that evolve over time to adapt to system and customers' evolving requirements. 

Knowledge and understanding:

After completing this course, students will have acquired: 

  • understanding of methods for designing large software systems
  • knowledge of how architectures can be modeled and analyzed.

Key skills:

After completing this module students will be able to:

  • design complex and large software systems using components and connectors
  • use UML as modeling language to represent the main concepts of software systems
  • document their main design decisions and motivate them in terms of quality attributes.

Course summary 

  • System architecture 
  • Service and network architectures 
  • Software architecture 
  • Architecture styles and patterns 
  • Architecture evolution 
  • Self-adaptive systems 

Prerequisite knowledge 

  • (required) Programming skills at CS bachelor level
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Dynamic Analysis and Deep Learning

Specific semester: 2nd
Number of credits: 6 ECTS 
InstructorAdil Khan, TA Youssef Youssry

Monitoring and dynamically analyzing complex systems and data is an essential asset for guaranteeing long-term reliability and stability of large systems, and for handling bug data to distill essential information to steer decision processes at all levels. 

The course provides the elements needed to understand and master the core technology to monitor large systems, extract information about the system behavior in terms of formal, probabilistic and statistic models. It provides core knowledge of modern machine and deep learning approaches to infer system properties and predict system evolution. 

Overall objective 
Analyzing large systems and data. 

Detailed objectives 

  • Understanding opportunities, limits, and goals of dynamic analysis and machine learning 
  • Learning main program, system, and data monitoring techniques 
  • Learning techniques for dynamically mining system models 
  • Learning machine learning approaches 
  • Learning deep learning approaches 
  • Understanding the main challenges of designing a framework for monitoring and analyzing complex systems 

Course summary 

  • Dynamic analysis and machine learning: opportunities and complementarities 
  • System monitoring 
  • Knowledge extraction and representations 
  • Dynamic analysis, inference of quasi-invariants and finite models 
  • Unsupervised learning, clustering, feature maps 
  • Supervised learning, classifiers, neural networks 
  • Concept mining, association rules, latent topics 

Prerequisite knowledge 

  • (required) Programming skills at CS bachelor level 
  • (required) Algorithms and data structure at CS bachelor level 
  • (required) Basics of static and probabilistic analysis at CS bachelor level 
  • (required) Discrete math at CS bachelor level 
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Master Thesis

Specific semester: 4th (classic track); 2nd, Summer, 3rd (fast track); summer after 4th semester (double degree program)
Number of credits: 30 ECTS (classic and fast tracks); 20 ECTS (double degree program)
InstructorMauro Pezzè

Learning objectives
The master thesis is a direct experience with a research, industrial or entrepreneurship project 

Course summary (mini-syllabus) 
The master thesis is an individual work carried on under the supervision of a SIT professor and can be: 

  • Research thesis: A research project carried on in a research laboratory either in SIT or in anther academic or industrial institution. A research thesis is a self-contained research project often part of a larger project.
  • Industry thesis: A project of industrial relevance carried on in cooperation with a company. An industry thesis shall be a self-contained project, usually part of a larger industry project, carried on under the co-supervision of an industrial advisor.
  • Start-up thesis: The definition of a start-up from a new idea. A start-up thesis shall produce a proposal to be submitted to investors. A start-up thesis is carried on with the co-supervision of an expert entrepreneur.

Classic and fast lane track
Master theses for classic and fast lane track are 30 ECTS courses (corresponding to an effort of 750 person/hours) to be carried on full time in the fourth semester for the classic master program and part time in the second and third semester and in the summers between the semesters). 

Double degrees
TO BE CONFIRMED WITH THE PARTNER INSTITUTIONS 

Master theses for double degrees are 20 ECTS courses (corresponding to an effort of 500 person/hours) to be carried on in the Summer after the third semester.

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System Protection

Specific semester: 3rd semester 
Number of credits: 6 ECTS 
Instructor: Giovanni Denaro 

Monitoring and dynamically analyzing complex systems and data is an essential asset for guaranteeing long term reliability and stability of large systems, and for handling bug data to distill essential information to steer decision processes at all levels. 

The course provides the elements needed to understand and master the core technology to monitor large systems, extract information about the system behavior in terms of formal, probabilistic and statistic models. It provides core knowledge of modern machine and deep learning approaches to infer system properties and predict system evolution. 

Overall objective 
Engineering and managing cybersecurity 

Detailed objectives 

  • Understanding system security
  • Security of the hardware and concrete infrastructure
  • Security of Wireless Networks
  • Cryptographic Protocols
  • Cryptography and digital signatures
  • Program Analysis for System Security + Reliability
  • Formal Methods for Information Security

Course summary 

  • System security
  • Security of the hardware and concrete infrastructure
  • Security of Web and wireless networks
  • Applied cryptography and quantum cryptography
  • Cryptographic Protocols
  • Digital signatures

Prerequisite knowledge 

  • (required) Programming skills at CS bachelor level
  • (required) Algorithms and data structure at CS bachelor level
  • (required) Basics of static and probabilistic analysis at CS bachelor level
  • (required) Discrete math at CS bachelor level
  • (required) Cyber protection (this master)
  • (required) Quality engineering (this master)
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Quantum Informatics

Specific semester: 3rd semester 
Number of credits: 3 ECTS 

Overall objective 
Learning the basic aspects of quantum computing, quantum programming and quantum cryptography. 

Detailed objectives 

  • Basic concepts of mathematics to understand quantum computing: Linear algebra: basis and linear independence, linear operators, scalar product, eigenvalues and eigenvectors
  • Information theory
  • Quantum computing and simulation
  • Quantum communications and post-quantum cryptography

Course summary 

  • Linear algebra, probability theory, and graph theory: recap of core concepts
  • Information theory: the Shannon theory
  • Quantum physics: the Bloch sphere and non-cloning theorem
  • Quantum computing and simulation: photonics, Maxwell demon, and Landauer principle
  • Classical and quantum computing models
  • Qubits, quantum gates, quantum measurements
  • Decoherence models and basics of quantum error correction
  • Adiabatic quantum computing and quantum annealing
  • Analogous quantum simulation, Hubbard and Ising models
  • Quantum cryptography and attacks (Shor and Grover algorithms), basic protocols (BB84)
  • Security proofs for quantum key distribution
  • Post-quantum cryptography algorithms. Hash-based signatures

Prerequisite knowledge 

  • (required) Linear Algebra at CS bachelor level
  • (required) Probability Theory at CS bachelor level
  • (required) Graph Theory at CS bachelor level
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Organizational Behavior and Industrial-Organizational Psychology

Specific semester: 1st semester 
Number of credits: 3 ECTS
Instructor: Prof. Dr. Thomas Maran

Course summary 

  • Psychology is the scientific field concerned with describing, explaining, and predicting human thought, feeling and behavior. Therefore, psychology is at the core of any attempt to understand organizational behavior and thus essential if the aim is to influence the behavior of people in organizations.
  • This course will introduce the basic principles of psychology. The human mind is thus described through the lens of cognition, emotion, motivation, and social processes. From this comprehensive understanding of human behavior, evidence-based, practical guidelines for personnel selection, performance management, and leadership are derived. After introducing the methods of psychology, the course moves on to teaching the logic behind business experiments and the evaluation of interventions.
  • At the end of the course, students will have a thorough understanding of the human mind and human behavior. In addition, students will be able to apply these basic principles of psychology to a variety of leadership and management challenges. The goal is to provide tomorrow's leaders with a technical background and the tools for evidence-based practice in leadership, thereby offering them new ways to think and organize their organizations.
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Product Design, Portfolio Management and Analytics

Specific semester: 2nd semester 
Number of credits: 6 ECTS
Instructor: Florian WangenheimSebastian Tillmanns, TA Theresa Schachner

The course “Product Design, Portfolio Management, and Analytics” focuses on key aspects of product management. Students will be introduced to (i) product design, (ii) portfolio management, and (iii) analytics: Product design includes the innovation process and innovative concepts such as smart products or solution selling. Portfolio management covers how products should be positioned in a competitive environment. In analytics, the course will emphasize cost calculations, pricing, and customer analytics. In the lecture, students will apply their knowledge to a variety of case studies.

Objectives and learning outcomes

Knowledge and understanding:

**After completing this course, students will have acquired:

  • A general understanding of product management
  • Knowledge about how to design successful products
  • Strategic and analytical skills for managing a product
  • Understand and handle challenges when managing products

Key skills:

After completing this module students will be able to:

  • Apply key instruments and concepts in order to successfully manage a product
  • Use their analytical skills to manage the costs, price, and customers of a product
  • Identify and anticipate innovative developments in product management
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Agile Leadership and Strategic Management

Specific semester: 2nd semester 
Number of credits: 3 ECTS
InstructorRoberto Quaglia, TA Paola Viotto

“Agile Leadership and Strategic Management” focuses on key strategic aspects of the strategic process, as well as strategic problem solving, alignment, engagement, and copying with black swans and paradigm shifts. The course draws on insights from a variety of fields – in particular, business strategy, problem solving, strategic communication, strategic planning, and strategic resilience.

Objectives and learning outcomes:

After completing this course, students will have acquired knowledge and understanding of:

  • The strategic process: from analysis, definition, planning, and evaluation
  • Hypothesis-driven problem solving
  • Pyramid principle strategic communication
  • Antifragile strategies

After completing this module students will be able to:

  • Assess and define business strategies
  • Be active contributors to the strategic planning process
  • Identify strategic statements and levels of ambition
  • Identify opportunities and threats on the external environment
  • Identify sources of competitive advantage as well as strategic strengths and weaknesses
  • Identify core challenges
  • Develop and communicate strategic initiatives

Course summary 

  • Charismatic Leadership, Visionary Leadership, and Vision Development, Guidelines for Goal Setting.
  • Innovation Leadership, Empowering Leadership und Shared Leadership, Guidelines for Delegating.
  • Integration: Guidelines for Ambidextrous Leadership (Case), Designing Structures to Fit Strategy, Organizational Culture.
  • Evidence-based Management, Agile Management Methods (Effectuation, Scrum, Lean, Start-Up, Design Thinking), Data-driven Decision Making, Business Experiments.
  • Strategic Analysis, Strategic Planning, and Goal Setting, Strategy Development, Implementation and Correction of Organisational Strategy.
  • Operational Planning and Control.
  • Strategic Management at the Business Unit and Company Level.
  • Guidelines for Strategic Leadership.
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Entrepreneurship and Intrapreneurship

Specific semester: 3rd semester 
Number of credits: 3 ECTS

Course summary 

  • Entrepreneurship Theory, Entrepreneurial Mindset, Digital Entrepreneurship.
  • Opportunity Recognition, Assessment of Entrepreneurial Opportunities, Business Modelling, The Founding Process, Finding Sources of Capital, Entrepreneurial Learning and Action Learning.
  • Entrepreneurial Growth, Valuation of Ventures.
  • Organizational Creativity and Innovation, Innovation Leadership, Empowerment, Performance Management, and Employee Creativity.
  • Forms of Corporate Venturing and Strategic Entrepreneurship, Business Model Innovation (Case), Innovation Management, Open Innovation, and Innovation Ecosystems.
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Transformational Change Management

Specific semester: 3rd semester 
Number of credits: 6 ECTS

Course summary 

  • Typifying Change and Transformation, Developing Organizations, Action Research Approach
  • Diagnosing Organizations, Planning Change, Visions of Change, Designing Interventions
  • Managing the Change Process, Change Leadership, Employee Participation, Guidelines for Implementing Change (Case, Digital Transformation), Outcome Evaluation
  • Organizational Learning, Learning Culture, Collective Intelligence, and Knowledge Structures, Team Diversity
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Product Vision, Strategy, Innovation and Marketing

Specific semester: 1st semester 
Number of credits: 6 ECTS
InstructorProf. Dr. Marc Gruber

Course summary 

  • Exploration and Exploitation in Organizations
  • Corporate Foresight, Roadmapping, and Product Visions
  • Market Opportunities for Technology: The Market Opportunity Navigator (Identification, Evaluation and Agile Focus Strategies)
  • New Product Development Processes & Organization: Closed & Open Innovation, Ecosystems
  • Building and Managing an Innovation Portfolio
  • Bringing New Technology to Market: Achieving Product-Market Fit and Lean Methodologies
  • Key Marketing Decisions in Product Innovation
  • The Diffusion of Innovation: Achieving Product Adoption
  • Profiting from Innovation: Business Models, Value Creation, and Value Appropriation
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The Master's program is designed and taught by top-class professors and researchers from all over the world and is inspired by Nobel prize holders and successful business leaders.

Teaching includes a combination of lectures, seminars, and blended e-learning, with lectures available at the SIT campus in Schaffhausen, Switzerland, broadcast live online or recorded for offline study. 

The institute encompasses a global community of prestigious high-ranking science and technology universities, featuring some of the best teaching support in the world. The course offers the unique option of graduating with a dual degree from one of SIT's partner institutes — the Carnegie Mellon University (CMU) in Pittsburgh, United States, or the National University of Singapore (NUS) in Singapore.

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Deep technical interdisciplinary knowledge is the cornerstone for technology leaders.

The master combines deep technical skills in software engineering and computing with multidisciplinary knowledge in technology for the future (quantum informatics and quantum cryptography).

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Familiarity with industrial-scale applications, business, and people is essential both for technology leaders in raising new companies and for scientists who want to contribute to modern society.

The master combines technology, hands-on skills, and actionable knowledge, like business science and science of people to build a new high-tech company or internal startup project.

Students will be required to undertake several compulsory and optional modules in addition to a thesis to complete the course. 

This thesis can be written based on the student's experience in their own startup business, or at one of SIT's business network partners such as Acronis, Citrix, Microsoft, and McKinsey & Company. 

Your research will be multidisciplinary and will allow you to choose in-depth optional modules from several of the following areas: 

  • Software engineering
  • Cybersecurity
  • Software verification
  • Business analysis
  • Artificial intelligence
  • Machine learning
  • Software quality
  • Data analytics
  • Cyberphysical systems
  • Distributed trust & blockchain
  • Mobile and wearable computing
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Proximity to top industries is a unique opportunity to seamlessly entering both industrial and academic careers. 

The SIT master in Computer Science and Software Engineering offers scholarships, internships and job opportunities thanks to an excellent network of supporting companies: 

  • Acronis
  • Parallels
  • Plesk
  • cPanel
  • Runa Capital
  • Acumatica
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Contemporary learning is a complex and fascinating activity that cannot be confined to classwork.

The master offers online courses, peer-to-peer meetings, on-campus collaborative projects, and practical activities for a holistic and efficient learning experience.

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The course offers the unique option of graduating with a dual degree from one of SIT's partner institutes:

  • CMU, Carnegie Mellon University (USA)
  • NUS, National University of Singapore (Singapore)
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Scholarships cover the full cost of the academic year at SIT partner schools Carnegie Mellon University or National University in Singapore.

Applications will open during the first semester and be reserved to SIT students.

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The course offers the unique option of graduating with a double degree from one of SIT's partner institutes:

  • CMU, Carnegie Mellon University (USA)
  • NUS, National University of Singapore (Singapore)
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Customer-centric Mindset and Agile Delivery Management

Instructor: Dr. Philip Zerrillo

Successful firms are forced to walk a tightwire between meeting market needs and creating organizational efficiencies. Just how they do this requires organization, insights, management understanding and determination. The modern manufacturing or service firm is simultaneously engaged in three core processes.

1) The design and development of products and services (BUILD),

2) The efficient and effective delivery of those products and services to the market (DELIVER), and

3) The process of gaining customers that wish to purchase those products and services or enter into transactions with the firm (CAPTURE).

How it organizes and the processes it adopts are key to a firm's ability to optimize these often divergent but highly interdependent activities. 
 
As markets, industries, economies and technologies have become more fluid, and cycles have become shorter the modern firm has been in search of greater agility. During this course, we will examine the key structures and processes to gain agility and overcome inertia. The roles or leadership, finance, supply-chain and the availability of firm information will be central to this portion of the course.