Python Bootcamp for Quant Finance

What Will You Learn?

• Python Fundamentals for Finance – Master Python basics, including data types, control structures, functions, and object-oriented programming to build a solid coding foundation.
• Data Manipulation with NumPy and Pandas – Learn to handle large datasets, perform data cleaning, filtering, grouping, and statistical computations efficiently.
• Data Visualization with Matplotlib and Seaborn – Create insightful charts, histograms, heatmaps, and other statistical plots to analyze financial and market data.
• Data Cleaning and Feature Engineering – Handle missing values, remove duplicates, detect outliers, and apply transformations like one-hot encoding and scaling for better model performance.
• Regression Modeling and Statistical Tests – Build and evaluate linear regression models while performing statistical tests like Durbin-Watson, Breusch-Pagan, and VIF to check assumptions.
• Machine Learning for Finance – Implement key ML models such as Decision Trees, Random Forest, and Support Vector Machines for predictive analytics in finance.
• Volatility Modeling in Equity Markets – Understand and apply models like ARCH, GARCH, and EWMA to analyze stock market volatility.
• Derivatives and Option Pricing Models – Explore financial derivatives, forward and futures contracts, and option pricing models like Black-Scholes, Binomial Tree, and Monte Carlo.
• Real-World Applications in Quantitative Finance – Apply Python skills to solve practical problems in risk management, trading strategies, and financial modeling.