Digital Finance — Classic Edition

Comprehensive BSc course covering FinTech, Blockchain, AI/ML, and Traditional Finance

4Modules 48Lessons 614+Charts 76Notebooks 48Mini-Lectures

Course Modules

Module 1

FinTech

12 lessons: Payments, Mobile Wallets, Neobanks, Open Banking, Digital Identity, P2P Lending, Robo-Advisors, InsurTech, RegTech, Regulatory Frameworks, Business Models

 Module 2

Blockchain

12 lessons: Hashing, Public Key Crypto, PoW, PoS, Bitcoin, Ethereum, Tokens, DeFi, Stablecoins, Security, Regulation & Future

 Module 3

AI / Machine Learning

12 lessons: Regression, Classification, Algorithmic Trading, Credit Scoring, Fraud Detection, NLP, Robo-Advisors, Market Prediction, Explainability & Bias

 Module 4

Traditional Finance

12 lessons: Financial Markets, Core Banking, Payment Rails, Electronic Trading, Market Microstructure, Risk Management, Derivatives, Wealth Management, CBDCs

Mini-Lectures

48 self-contained 10-slide summaries — one per lesson, ideal for quick review or flipped-classroom prep. Each mini-lecture distills the key concepts into a concise standalone deck.
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Interactive

12 Python Demos

Hands-on demos across all 4 modules: payment calculators, block structures, ML classifiers, efficient frontiers

 Projects

6 Student Projects

Streamlit apps and Jupyter notebooks: Finance Dashboard, Blockchain Explorer, Credit Risk, Trading Backtester, DeFi Analyzer, Fraud Detection

 PhD

PhD Seminar

12 advanced research-level lessons across 4 themes: Market Design, ML & Prediction, DLT, Regulation & Society

Assessment Tracks

Technical Track

Build a working Streamlit application with ML components. Graded on code quality, functionality, and documentation.

Research Track

Write a research paper analyzing a Digital Finance topic with quantitative analysis and literature review.

Business Track

Develop a business case or strategy proposal for a FinTech innovation with market analysis.