Learning Library

Welcome to Learning Library! Explore our collection of educational courses and tutorials. Each subject contains comprehensive lessons organized by chapters, with quizzes to test your understanding.

Quantitative Finance Theory

Probability theory and stochastic processes for quantitative finance

Quant Research

A comprehensive tutorial series for learning probability theory for quantitative finance and algorithmic trading

For: quantitative developers and software engineers transitioning to quant roles

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Mathematical Foundations

Applied statistics, numerical methods, and linear algebra

Applied Statistics

Learn applied statistical methods for quantitative developers, focusing on practical analysis and inference

For: quantitative developers and software engineers who need practical statistical skills

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Developer

Programming tools, operating systems, concurrency, performance, and networking

Python Pandas

Learn Python Pandas for data manipulation and analysis

For: developers and data analysts working with tabular data

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Tools & Editors

Master the essential tools for efficient software development

Vim

Master Vim, the powerful modal text editor for efficient code editing

For: software engineers who want to edit code faster and more efficiently

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Quant Development Projects

Project-based path: backtester, paper trading bot, and ML trading strategy

Project 1: Backtesting Engine

Build a simple, reliable backtesting system from scratch with Python and Pandas

For: software engineers and quant developers learning algorithmic trading

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Project 2: Paper Trading Bot

Extend the backtester into a real-time paper trading bot using broker APIs

For: developers who have completed Project 1 and want live paper trading

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Project 3: ML Trading Strategy

Add predictive models to the trading workflow and execute via the paper bot

For: developers who have completed Projects 1–2 and want ML-driven signals

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