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Mastering Financial Engineering: Quantitative Analysis and Risk Management

About Course
Have you ever thought, about what would happen if you combine the principles of Financial Engineering with the power of Artificial Intelligence and Machine Learning? Well, you can stop imagining and start working towards your goal.
This course combines the principles of Financial Engineering with Artificial Intelligence and Machine Learning, providing a comprehensive understanding and innovative approaches for navigating the evolving financial landscape
- Regression models.
- Classification models.
- Unsupervised learning.
- Q-learning and reinforcement learning.
*VIP SECTION*
- Trading using algorithms (including methods based on Machine Learning, Trend-Following, and Q-learning).
- Models for statistical factors.
- Utilising HMMs to detect regimes and model volatility clustering.
We’ll find out about the greatest mistake made in the last decade by marketing representatives acting as “Machine Learning Specialists” who promised to instruct naive students on how to “predict stock prices with LSTMs.” You will discover the precise reasons behind their methodology’s basic flaws and the absurdity of their findings. It serves as a cautionary tale on how not to use AI in finance.
If you enjoy finance or artificial intelligence, or both—should take this course, whether you’re a professional, a student, or someone looking to better your career.
Course Content
Getting Started
Introduction and course overview.
08:53Data links and practical coding experience.
00:00Learn to use Github + additional coding tips (Optional).
00:00Where to download the data, code, and notebooks.
00:00Strategies for successfully completing this course.
00:00