Curriculum
The choice of elective courses makes it possible for students taking the certificate to get a combined deep knowledge in the four main fields relevant to FinTech applications: F(Financial Technology), T (Technological and methodological skills related to Artificial Intelligence and Machine Learning), D (Computer programming with emphasis on programming languages useful in FinTech) and B (Digital businesses and digital value creation for financial services and products).
In order to achieve its educational objective, the FinTech Certificate programme offers two types of Master’s courses:
- Two compulsory courses focusing on FinTech (8 ECTS credits in total).
- Four categories of compulsory elective courses in the remaining areas of T, D and B. Ideally, the FinTech students will take at least one course from each category. (16 ECTS credits in total)
To successfully complete the FTC, students should earn a total of 24 ECTS credits.
| Number | Name | Lecturer | Semester | ECTS | Host |
| 7,590 | Fintech - Economics and Technology | Gruber Peter | Autumn | 4 | FinTech |
| 8,590 | Fintech Seminars | Georg Co-Pierre | Spring | 4 | FinTech |
| Number | Name | Lecturer | Semester | ECTS | Host |
| 7,040|8,023 | RPV: Design Thinking for Artificial Intelligence | Hehn Jennifer van Giffen Benjamin | A & S | 8 | MBI |
| 7,044 | Introduction to Artificial Intelligence and Machine Learning | Mommert Michael | A | 6 | MBI |
| 7,235 | Decision Making under Risk and Uncertainty | Biener Christian | A | 4 | MBI |
| 7,230 | Introduction to Machine Learning and Deep Learning | Borth Damian | A | 4 | MUG |
| 7,310 | Data Analytics I: Predictive Econometrics | Marekova Jana | A | 4 | MiQEF |
| 7,325 | Smart Data Analytics | Härdle Wolfgang | A | 4 | MiQEF |
| 7,375 | 8,380 | Quantitative Text Analysis | Gava Roy | S | 4 | MIA |
| 7,682 | Medien/Media: Big Data, Artificial Intelligence and the Algorithmic Society | Barassi Veronica | A | 6 | KTX |
| 7,852 | Human Computer Interaction | Schöning Johannes | A | 6 | MCS |
| 8,024 | FPV: Big Data und Data Science - Intelligente Datenprodukte entwickeln (not FS24) | Blohm Ivo | S | 4 | MBI |
| 8,048 | Introduction to Artificial Intelligence and Machine Learning (not FS24) | Borth Damian | S | 6 | MBI |
| 8,274 | Corporate Finance, Banking and Venture Capital | Häfner Samuel, Keuschnigg Christian | S | 4 | MEcon |
| 8,330 | Machine Learning (MiQEF) | Preinerstorfer David | S | 4 | MiQEF |
| 8,334 | Game Theoretic Models for a Digital World | Gizatullina Alia | S | 4 | MiQEF |
| 8,380 | Quantitative Text Analysis | Gava Roy | S | 4 | MIA |
| Number | Name | Lecturer | Semester | ETCS | Host |
| 7,162 | Financial Programming with Matlab | Schürle Michael Hermann | A | 4 | MBF |
| 7,264 | Data Handling: Databases | Venturini Marco | A | 4 | MEcon |
| 7,781 | Skills: Julia - A Fresh Approach to Numerical Computing | Söderlind Paul | A | 3 | KTX |
| 7,789|8,789 | Skills: Programming with Advanced Computer Languages | Silic Mario | A & S | 3 | KTX |
| 7,854 | Data Science | Handschuh Siegfried | A | 6 | MCS |
| 7,856 | Advanced Software and Systems Engineering | Mayer Simon Barbara Weber | A | 6 | MCS |
| 7,858 | Advanced Databases | Niklaus Christina | A | 6 | MCS |
| 7,926 | Introduction to Machine Learning in R | Stachl Clemens | A | 6 | CEMS |
| 8,016 | Methoden: Big Data und Data Science | Blohm Ivo | S | 6 | MBI |
| 8,017 | Engineering Software Systems (not FS24) | Salvaneschi Guido | S | 4 | MBI |
| 8,060 | Web Data and Digital Analytics (not FS24) | Hildebrand Christian | S | 4 | MiMM |
| 8,273 | Multivariate Statistical Analysis with Python | Fengler Matthias | S | 4 | MEcon |
| 8,780 | Skills: Network Analysis and Visualization with R & Python | Hoffmann Magnus | S | 3 | KTX |
| 8,338 | Introduction to Web Mining for Social Scientists (not FS24) | Matter Ulrich | S | 4 | MiQEF |
| 8,785 | Skills: Data Security and Privacy | Mitrokotsa Katerina | S | 3 | KTX |
| 9,014 | Introduction to Software Engineering | Salvaneschi Guido | A | 6 | MBI |
| 9,015 | Cryptography (not FS24) | Mitrokotsa Katerina | S | 6 | MBI |
| Number | Name | Lecturer | Semester | ETCS | Host |
| 7,008 | RPV: Data Science - Methods and Technologies for Data-driven Business Models | Wulf Jochen Andreas | A | 4 | MBI |
| 7,017 | Cybersecurity and Privacy | Mitrokotsa Katerina | A | 3 | MBI |
| 8,032 | Methods: Social Network Analysis - a Systematic and Quantifying Approach | Shahrezaye Morteza | S | 3 | MBI |
| 7,041 | Fintech Innovation in Singapore and Southeast Asia (FISSA) | Njavro Mato | A | 3 | MBI |
| 7,048 | Value Creation with (Big) Data - Enterprise Solutions and Technologies for Text Analytics | Back Andrea | A | 3 | MBI |
| 7,260 | Industrial Organization and Digitalization | Bühler Stefan | A | 4 | MEcon |
| 7,377 | Introduction to Cryptography and Cybersecurity | Horlemann Anna-Lena | A | 4 | MIA |
| 7,850 | Cyber Security | Mitrokotsa Katerina | A | 6 | MCS |
| 8,210 | Digital Business and Transformation (not FS24) | Ebel Philipp Alexander | S | 4 | SIM |
| 8,027 | Ubiquitous Computing and the Internet of Things | Mayer Simon | S | 3 | MCS |
| 8,288 | Blockchain Markets | Häfner Samuel | S | 4 | MEcon |
| 8,711 | Recht/Law: Wirecard, Datenanalytik, Vertrauen und Kontrolle - Warnsignale erkennen | Schuchter Alexander | S | 3 | KTX |
| Number | Name | Lecturer | Semester | ECTS | Host |
| 9,165 | Financial Technlogy (MBF) | Barbon Andrea | A | 4 | MBF |
