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This six-week Python for Finance course is designed to equip learners with the essential programming skills needed for financial analysis, data handling, and automation. In Week 1, students will be introduced to Python programming, covering fundamental concepts such as syntax, data types, operators, and data structures like lists and tuples. They will also learn to navigate Jupyter Notebook and manage Python files effectively. Week 2 delves into core Python concepts, including conditional statements, loops, functions, and file handling. Students will gain hands-on experience in importing and managing external libraries for data manipulation. From Week 3, the course shifts focus to financial applications, introducing NumPy and Pandas for working with financial datasets. Students will explore time-series data, stock market data retrieval, and basic statistical analysis. Week 4 covers data visualization techniques, helping learners understand stock price movements, technical indicators, and portfolio trends using Python libraries. Week 5 introduces financial computations, including time value of money, risk and return analysis, portfolio optimization, and asset allocation. Participants will explore key financial metrics like Sharpe Ratio, Maximum Drawdown, and the Markowitz Efficient Frontier. Finally, in Week 6, students will learn to automate financial tasks, build simple financial models, and perform sentiment analysis for investment insights. By the end of this course, learners will be proficient in using Python for financial data analysis, risk assessment, and decision-making, making them well-equipped for careers in finance, fintech, and data analytics.
