Learning Library
Free courses and practical ebook-based resources in finance, programming, data analysis, machine learning, and AI.
Getting Started with Python
Learn Python fundamentals: syntax, data types, and basic programming concepts.
Getting Started with R Programming
Learn R basics including syntax, data types, and RStudio.
Python for Data Science
NumPy, data structures, and essential tools for data science.
Data Manipulation Using Pandas
Master Pandas for data wrangling and analysis.
R Programming for Data Science
Data manipulation with dplyr, tidyr, and the tidyverse.
Data Visualization with R
Learn how to create beautiful data visualizations in R using Base R graphics and ggplot2
Introduction to Machine Learning
ML fundamentals: concepts, workflow, and key algorithms.
Machine Learning in Finance Using Python
Apply ML algorithms to financial prediction problems using Python and scikit-learn.
Credit Risk Modelling in R
Build credit scoring models using R - from data prep to scorecard deployment.
Financial Time Series Analysis in R
Analyze and forecast financial time series data.
Portfolio Analysis in R
Portfolio optimization and performance analysis.
Investment Risk and Return Analysis in Python
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.
Quantitative Trading Strategies in R
Build and backtest systematic trading strategies.
Derivatives with R
Price and analyze options and other derivatives.
SQL for Data Analysis - Foundations
A practical guide to SQL for analysts. Learn to query data, join tables, build summaries, and write the SQL that answers real business questions.
Everything You Need to Learn
A focused learning library for finance professionals who want practical data and AI skills.
Built for Finance
Examples and lessons are grounded in finance topics, datasets, and workflows.
Focused Library
Browse the current learning library directly and start with what is available now.
Practical Focus
Learn concepts through applied examples you can connect back to finance work.
Code & Templates
Use course code, datasets, and templates as a starting point for your own analysis.
Self-Paced Learning
Work through lessons on your own schedule, course by course.
Immediate Access
Start with free lessons or get individual ebooks when you need the full material.
The finance professionals who thrive in the next decade won't just understand data and AI. They'll know how to build, analyze, and automate.
Who this is for
Finance is being transformed by data science, machine learning, and AI. The professionals who thrive will be those who can work confidently with these tools, not just understand the concepts.
This platform is for finance professionals who want to acquire practical technical skills without wading through generic programming tutorials. Lessons are built around financial applications, from Python and R to credit risk, portfolio analysis, visualization, and AI workflows.
Whether you're an analyst, portfolio manager, risk professional, or working in another finance role, you can use the catalog to learn the skills most relevant to your work.