Financial Engineering and AI with Python: Portfolio and Trading Systems

Bridging the gap between traditional finance and modern artificial intelligence is one of the most valuable skills in today's data-driven economy. This text-based course guides you through the foundational concepts of financial engineering and demonstrates how to supercharge them using Python and machine learning. You will transition from understanding basic financial metrics to building robust, automated trading strategies and portfolio optimization models. By working through clear explanations and structured code walkthroughs, you will gain a deep, practical understanding of how mathematical models apply to real-world market data. What you'll learn: - Understand core financial concepts, including asset returns, risk metrics, and the Capital Asset Pricing Model (CAPM). - Analyze time series data using statistical models like ARIMA and smooth trends with moving averages. - Optimize investment portfolios using mathematical programming to maximize the Sharpe ratio on the efficient frontier. - Build algorithmic trading strategies based on trend-following indicators and reinforcement learning principles. - Apply modern Python data tools and clean coding practices, including type hints and efficient dataframe operations, to financial datasets. - Detect market regimes and model volatility clustering using unsupervised machine learning techniques. The curriculum starts with foundational financial theory and basic data analysis before advancing to statistical modeling, portfolio mathematics, and intelligent trading algorithms. You will progress step-by-step through written explanations and code examples designed to build your confidence. This course is designed for aspiring quantitative analysts, finance professionals, and programmers who are new to financial engineering. No prior background in finance or advanced machine learning is required, though basic Python familiarity is helpful. Start reading today to master the intersection of finance and artificial intelligence.