Optional Primers: Introduction to Investment Finance, Introduction to Financial Mathematics, Introduction to Probability & Statistics, Introduction to Programming (Python).
Probability Theory, Basic Stochastic Processes, Brownian Motion, Stochastic Calculus, Black-Scholes-Merton Models.
Machine Learning for Quantitative Finance, Monte Carlo Simulation Methods, Numerical Methods for Partial Differential Equations both theory and implementation in Python.
Valuation of Equity Derivatives, Interest Rate Derivatives, Currency Derivatives, Credit Derivatives, Swaps both deep understanding of the models and learning the practical implementation and modeling in Python.
Coverage of Financial Risk Management areas, Market Risk, Credit Risk, Operational and Compliance Risk etc. both theory plus practical modeling.