Portfolio optimization is a powerful technique in finance, and Python makes it accessible and efficient. In this hands-on case study, you’ll use your data analysis skills to work through a real-world example: analyzing and optimizing a portfolio of four stocks. You’ll start by building an equal-weighted portfolio and evaluating its performance using key financial metrics like daily returns and the Sharpe ratio. Then, you’ll generate 10,000 portfolio scenarios with different stock weightings and use Python to find the optimal combination with the highest Sharpe ratio. Along the way, you’ll use data visualization to explore results and reinforce your understanding of portfolio performance. This course is the perfect next step for learners who want to apply their Python knowledge to finance.

In addition, you will gain practical experience in translating theoretical portfolio concepts into actionable Python workflows. By the end of the case study, you will be able to confidently simulate, evaluate, and optimize investment portfolios using data-driven techniques commonly used in quantitative finance.