Finance TrainFinance TrainFrom valuation and risk to Python, R and machine learning. Practical ebooks and articles for finance professionals who want to understand the numbers and build with them.
Each one is a complete PDF with every code and data file. The first chapter is free to read here.
Learn how to create beautiful data visualizations in R using Base R graphics and ggplot2
Learn how to evaluate investment risks and returns using Python. Covers financial risk fundamentals, return calculations, statistical measures (mean, variance, skewness, kurtosis), and practical analysis techniques for real-world investment data.
PDF ebook with all code and data files.
Best value
Ten R and Python ebooks together, for $29.
8 chapters
9 chapters
February 25, 2026 · Chapter
Machine learning has become one of the most influential technologies in modern computing. It represents a fundamental shift in how we approach problem-solving with computers. Rather than explicitly programming rules for a computer to follow, we provide data and let the computer discover the rules itself.
February 6, 2026
January 7, 2026 · Chapter
Investing in financial markets always involves some level of risk, and understanding the relationship between risk and return is crucial for investors. Risk refers to the uncertainty of the outcome of an investment, while return refers to the profit or loss generated by an investment over time. Investors expect to be compensated for taking on additional risk. Let’s understand the concepts of investment risk and return in more detail.
January 3, 2026
Learn to use Jupyter notebooks for interactive coding, data analysis, and sharing your work.
January 3, 2026
A practical comparison for finance professionals deciding between Python and R for data science and analytics.
December 23, 2025
A practical guide to the math concepts behind data science—what you actually need to know as a finance professional, and what the libraries handle for you.