Financial Engineering and Artificial Intelligence in Python

Have you ever thought about what would happen if you combined the power of machine learning and artificial intelligence with financial engineering. Today, you can stop imagining, and start doing. This course will teach you the core fundamentals of financial engineering, with a machine learning twist.

We will cover must-know topics in financial engineering, such as:Exploratory data analysis, significance testing, correlations, alpha and betaTime series analysis, simple moving average, exponentially-weighted moving averageHolt-Winters exponential smoothing modelARIMA and SARIMAEfficient Market HypothesisRandom Walk HypothesisTime series forecasting ("stock price prediction")Modern portfolio theoryEfficient frontier / Markowitz bulletMean-variance optimizationMaximizing the Sharpe ratioConvex optimization with Linear Programming and Quadratic ProgrammingCapital Asset Pricing Model (CAPM)Algorithmic trading (VIP only)Statistical Factor Models (VIP only)Regime Detection with Hidden Markov Models (VIP only)In addition, we will look at various non-traditional techniques which stem purely from the field of machine learning and artificial intelligence, such as:Regression modelsClassification modelsUnsupervised learningReinforcement learning and Q-learning***VIP-only sections (get it while it lasts. ) ***Algorithmic trading (trend-following, machine learning, and Q-learning-based strategies)Statistical factor modelsRegime detection and modeling volatility clustering with HMMsWe will learn about the greatest flub made in the past decade by marketers posing as "machine learning experts" who promise to teach unsuspecting students how to "predict stock prices with LSTMs". You will learn exactly why their methodology is fundamentally flawed and why their results are complete nonsense.

It is a lesson in how not to apply AI in finance. As the author of ~30 courses in machine learning, deep learning, data science, and artificial intelligence, I couldn't help but wander into the vast and complex world of financial engineering. This course is for anyone who loves finance or artificial intelligence, and especially if you love both.

Whether you are a student, a professional, or someone who wants to advance their career - this course is for you. Thanks for reading, I will see you in class. Suggested Prerequisites:Matrix arithmeticProbabilityDecent Python coding skillsNumpy, Matplotlib, Scipy, and Pandas (I teach this for free, no excuses.