Entry points, 1st year, Common Courses
Academic year 2023/2024
University of Rennes 1 (UR1)
Programme Lead: Alvaro Pina Stranger, alvaro.pina-stranger@univ-rennes1.fr
FIRST SEMESTER
| Courses | ECTS |
| Innovation and Entrepreneurship / Fintech Basics | 5 |
| Business Development Laboratory 1 | 5 |
| Introduction to Finance | 5 |
| Basics of Data Analysis | 6 |
| Advance Data Bases | 4 |
| Object-oriented Analyses and Design | 5 |
SECOND SEMESTER
| Courses | ECTS |
| Business Development Laboratory 2 | 5 |
| Knowledge and Intangible Assets Management - KNI | 5 |
| FinTech Business Cases | 5 |
| Machine Learning 1 | 5 |
| Semantic Web Technologies | 5 |
| Database Security | 5 |
University of Trento (UNITN)
Programme Lead: Sandro Luigi Fiore, sandro.fiore@unitn.it
FIRST SEMESTER
| Courses | ECTS |
| Innovation and Entrepreneurship Basic | |
| Introduction to Computer and Network Security | |
| Machine Learning | |
| Web Architectures | |
| Concurrency | |
| International Accounting and Finance I: International Accounting 2 | |
| Statistical Methods | |
| High-Performance Computing for Data Science |
SECOND SEMESTER
| Courses | ECTS |
| Business Development Laboratory | 9 |
| ICT Innovation (includes EIT Digital Summer School) | 9 |
| Cyber Security Risk Assessment | |
| Deep Learning | |
| Distributed Systems 1 | |
| International Accounting and Finance II: International Corporate Finance 2 | |
| Workshop on Financial Simulation | |
| Statistical Models | |
| Bio-Inspired Artificial Intelligence | |
| Autonomous Software Agents | |
| Blockchain |
Eötvös Lorand University (ELTE)
Programme Lead: Molnár Bálint, molnarba@inf.elte.hu
FIRST SEMESTER
| Courses | ECTS |
| I&E Basics | 5 |
| Principles of Artificial Intelligence | 5 |
| Introduction to Computer Security | 5 |
| Introduction to Data Sciences | 5 |
| Introduction to Finance | 5 |
| Business Development Lab I. | 5 |
SECOND SEMESTER
| Obligatory Courses | ECTS |
| Business Development Lab II. | 5 |
| Information Security Management | 6 |
| Management Skills for Tech Entrepreneurs | 5 |
| Service Science | 5 |
| Machine Learning | 5 |
| Summer Schools with I&E project | 4 |
Technical University of Madrid (UPM)
Programme Lead: Alejandro Rodríguez González, alejandro.rg@upm.es
FIRST SEMESTER
| Courses | ECTS |
| Introduction to Innovation and Entrepreneurship management | 6 |
| Fundamentals of Finance | 6 |
| Blockchain and Services for Fintech Enterprise Integration | 5 |
| Requirements Engineering | 6 |
| Software Verification and Validation | 6 |
SECOND SEMESTER
| Courses | ECTS |
| Introduction to Technology Watch and Competitive Intelligence | 1 |
| I&E Seminars | 5 |
| Entrepreneurship and Business Modelling | 6 |
| Launching of ICT Product/Services to the Market | 2 |
| Data Mining | 4 |
| Seminars on Systems for Finance | 4.5 |
| Programming for Data Processing | 4.5 |
| Summer School | 4 |
Polytechnic University of Milan (POLIMI)
Programme Lead: Federico Schiepatti, federico.schiepatti@polimi.it
FIRST & SECOND SEMESTER
| Technical Major (21 ECTS) | ECTS |
| Data Bases 2 - I semester | 5 |
| Software Engineering 2 - I semester | 5 |
| Computing Infrastructures - II semester | 5 |
| Machine Learning - II semester | 6 |
| Elective Courses (3 choices, 15 ECTS) | |
| First semester: Recommender Systems, Data Mining and Text Mining, Advanced Algorithms and Parallel Programming, Data Intelligence Applications, Artificial Neural Networks and Deep Learning | |
| Second semester: Financial Risk Management, Computer Security, Cryptography and Architectures for Computer Security | |
| I&E Minor - Innovation & Entrepreneurship courses (24 ECTS) | |
| Strategy and Marketing - I semester | 10 |
| Financial Markets and Institutions - I semester | 5 |
| Digital Innovation Lab - II semester | 5 |
| I&E Summer School | 4 |
POLIMI, as entry university, is best suited for applicants with a bachelor degree in Computer Engineering (or similar programmes). It means having a strong base of ICT, computer science, programming and engineering courses in your transcript of records, including physics and math courses at academic level.
Exit points, 2nd year, Specialisation
Academic year 2024/2025
University of Rennes 1 (UR1)
Programme Lead: Alvaro Pina Stranger, alvaro.pina-stranger@univ-rennes1.fr
SPECIALISATION: Fintech for Social Impact and Financials
Rennes 1 will provide specialisation contents oriented to advanced data management, using scalable data analytics methods and techniques. Some of these techniques are distributed data management, distributed and parallel query processing, NoSQL technologies, NewSQL technologies, complex event processing, scalable data management ecosystems, and cloud infrastructure, specifically, computing and storage, and elastic management. The exit year specialisation at Rennes 1 can be addressed from two perspectives: on the one hand, students can adopt a stand towards social impact, this is, bearing in mind that Fintech applications may have a positive impact on society, especially, by democratising financial knowledge and granting access to a wide array of financial tools. On the other hand, students can adopt a stand towards financials, specifically, through the use of Bloomberg specialised services, which remains at the cutting edge of innovation by delivering fast access to indispensable news, data and trading tools.
THIRD SEMESTER
| Courses | ECTS |
| I&E Study on Fintech | 6 |
| Fintech Project | 4 |
| Data Mining | 5 |
| Machine Learning 2 | 5 |
| Dataware Houses | 3 |
| Cloud and Big Data Management | 3 |
FOURTH SEMESTER
| Courses | ECTS |
| Master Thesis | 30 |
University of Trento (UNITN)
Programme Lead: Sandro Luigi Fiore, sandro.fiore@unitn.it
SPECIALISATION: Distributed Fintech systems
The specialisation will provide content oriented towards distributed FinTech systems that uses advanced machine intelligence and distributed algorithms while providing open and secure access. It includes courses in advanced learning methods, advanced distributed secure systems (blockchain and consensus, cryptography and zero knowledge) and evolutionary algorithms and AI and key notions of financial risks managements and markets.
THIRD SEMESTER
| Courses | ECTS |
| Innov. & Entrepreneurship Studies in ICT | |
| Concurrency | |
| (Financial) Risk management | |
| Financial Markets and Economic Activity | |
| Data Mining | |
| Research Project (in alternative to any of the above) |
FOURTH SEMESTER
| Courses | ECTS |
| Company internship | 6 |
| Master Thesis | 24 |
Université Côte d'Azur (UCA)
Programme Lead: Francoise BAUDE, Francoise.BAUDE@univ-cotedazur.fr
SPECIALISATION: Fintech for Financial and Insurance Business
The specialisation will provide content oriented towards Financial or Insurance institution's needs, related to their common B2C activities but also to their investment activities on financial markets. This means courses content will include an introduction to financial markets, some mathematical and digitalised tools for modelling how financial products are priced and traded on such markets, and how associated risks can be covered. The rest of the program courses is devoted to typical subjects needed in FinTech: distributed systems, security, data science, etc.
THIRD SEMESTER
| Courses | ECTS |
| l&E Study | 6 |
| Models and Computation for Risk Coverage | 6 |
| Elective in Security | 2+2 |
| Project in Fintech | 6 |
| Elective in CS (Big Data, Cloud, Distr. Systems, Data Science, Web Science) | 2+2+2+2 |
FOURTH SEMESTER
Company internship and Master Thesis (30 ECTS)
Eötvös Lorand University (ELTE)
Programme Lead: Molnár Bálint, molnarba@inf.elte.hu
SPECIALISATION: Systems Engineering for Financial Technologies
The specialisation will provide content oriented towards 'Systems Engineering for Financial Technologies'. It includes courses in Consultation for Dissertation (Fintech Lab.), Development of Financial IT Systems, Advanced Machine Learning, Cryptography, Business Intelligence and Data Visualization, among others.
THIRD SEMESTER
| Courses | ECTS |
| Fintech. Lab I. | 4 |
| I&E Study | 6 |
| Advanced Machine Learning | 5 |
| Cryptography | 6 |
| Development of Financial IT Systems | 5 |
| Business Intelligence and Data Visualisation | 4 |
FOURTH SEMESTER
| Courses | ECTS |
| Master Thesis | 30 |
