The choice of elective courses makes it possible for students taking the certificate to get a combined deep knowledge in the three main fields relevant to FinTech applications: 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).
Students will ideally choose at least one compulsory elective course in each category in the T, D and B areas.
COMPULSORY: FINANCE (F)
| Number |
Name |
Lecturer |
Term |
ECTS
|
Host
|
9,165
|
Financial Technology |
Andrea Barbon
|
Autumn
|
4
|
MBF
|
7,010
|
Fintech Seminars |
Angelo Ranaldo
|
Spring
|
4 |
FinTech
|
COMPULSORY ELECTIVES: TECHNOLOGY AND METHODOLOGY (T)
| Number |
Name
|
Lecturer
|
Term
|
ECTS
|
Host
|
| 7,021 |
Human-Computer Interaction (MBI) |
Schöning Johannes |
A |
3 |
MBI |
| 7,040 |
RPV: Design Thinking for Artificial Intelligence |
Hehn Jennifer |
A |
8 |
MBI |
| 7,044 |
Introduction to Artificial Intelligence and Machine Learning |
Borth Damian |
A |
6 |
MBI |
| 7,235 |
Introduction to Machine Learning and Deep Learning |
Borth Damian |
A |
6 |
MUG |
| 7,310 |
Data Analytics I: Predictive Econometrics |
Jana Marekova |
A |
4 |
MiQEF |
| 7,325 |
Smart Data Analytics |
Härdle Wolfgang |
A |
4 |
MiQEF |
| 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 |
| 8,048 |
Introduction to Artificial Intelligence and Machine Learning |
Borth Damian |
S |
6 |
MBI |
| 8,330 |
Machine Learning (MiQEF) |
David Preinerstorfer |
S |
4 |
MiQEF |
| 8,380 |
Quantitative Text Analysis |
Gava Roy |
S |
4 |
MIA |
COMPULSORY ELECTIVES: DATA SCIENCE (D)
| Number |
Name |
Lecturer |
Term |
ETCS |
Host |
| 7,046 |
Introduction to Computer Systems and Networks |
Mayer Simon |
A |
6 |
MBI |
| 7,162 |
Financial Programming with Matlab |
Schürle Michael |
A |
4 |
MBF |
| 7,264 |
Data Handling: Databases |
Grossniklaus Michael |
A |
4 |
Mecon |
| 7,781 |
Skills: Julia - A Fresh Approach to Numerical Computing |
Söderlind Paul |
A |
3 |
KTX |
| 7,789 |
Skills: Programming with Advanced Computer Languages |
Silic Mario |
A |
3 |
KTX |
| 7,854 |
Data Science |
Handschuh Siegfried |
A |
6 |
MCS |
| 7,856 |
Advanced Software and Systems Engineering |
Mayer Simon |
A |
6 |
MCS |
| 8,017 |
Engineering Software Systems |
Salvaneschi Guido |
S |
4 |
MBI |
| 8,060 |
Web Data and Digital Analytics |
Hildebrand Christian |
S |
4 |
MiMM |
8,273
|
Multivariate Statistical Analysis with Python
|
Fengler Matthias
|
S
|
4
|
MEcon
|
| 8,338 |
Introduction to Web Mining for Social Scientists |
Matter Ulrich |
S |
4 |
MiQEF |
| 9,014 |
Introduction to Software Engineering |
Salvaneschi Guido |
S |
6 |
MBI |
| 9,015 |
Cryptography |
Mitrokotsa Katerina |
S |
6 |
MBI |
COMPULSORY ELECTIVES: BUSINESS APPLICATIONS (B)
| Number |
Name |
Lecturer |
Term |
ETCS |
Host |
| 7,008 |
RPV: Data Science - Methods and Technologies for Data-driven Business Models |
Wulf Jochen Andreas |
A |
4 |
MBI |
| 7,010 |
RPV: Industry 4.0 and Digital Value Creation |
Hofmann Erik |
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 |
Grüttner Arne |
A |
3 |
MBI |
| 7,260 |
Industrial Organization and Digitalization |
Bühler Stefan |
A |
4 |
Mecon |
| 7,850 |
Cyber Security |
Mitrokotsa Katerina |
A |
6 |
MCS |
| 8,027 |
Ubiquitous Computing and the Internet of Things |
Mayer Simon |
S |
3 |
MCS |