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Full Course (1.30 GB).
Python for Quant Trading Course Pack
Unlock the power of Python programming and quantitative trading with this comprehensive course pack. You’ll receive two complete courses designed to take you from Python fundamentals to advanced quant trading strategies, with hands-on coding and backtesting exercises.
Course 1: Python Fundamentals for Quant Trading
Master Python basics tailored specifically for quantitative finance. This course covers:
Introduction & Setup
Installing Anaconda
Jupyter Notebook walkthrough
Python Basics
Variables, data types, and arithmetic operations
Loops, conditional statements, and logical operators
Functions and classes fundamentals
Pandas Library
Loading and manipulating financial data
Working with datetime indexes
Rolling window functions for time series
Technical Indicators & Strategy Backtesting
Downloading market data
Calculating key technical indicators
Building and backtesting your first trading strategy
Strategy performance metrics and course wrap-up
Course 2: Quant Trading Strategies with Python
Take your skills to the next level by developing, backtesting, and optimizing real quant trading strategies:
Introduction & Setup
Meet your instructor and course overview
Installing Python packages and setting up the environment
Backtesting Essentials
Why backtesting matters
Tools and rules for high-quality backtests
Using the Backtrader platform: data feeds, orders, exits, commissions, and analyzers
Strategy Development
Generating trading ideas and integrating indicators
Incorporating machine learning concepts
Step-by-step strategy building
Feature Engineering & Data Preparation
Extracting and preparing features from financial data
Weekly regime and daily options feature modeling
Calculating comprehensive technical indicators
Backtesting & Visualization
Building your own backtester
Visualizing strategy results and metrics
Strategy Optimization
Dynamic stop-loss techniques
Pattern-based intraday price action strategies
Parameter tuning for optimal results
Out-of-Sample Testing
Validating strategy robustness on new data
This pack is perfect for traders, quants, or developers eager to harness Python for financial markets, combining theory with hands-on projects to build practical skills.
