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Python Crypto Trading Bot: Build, Backtest & Deploy
Rating: 4.5 out of 5(38 ratings)
158 students

Python Crypto Trading Bot: Build, Backtest & Deploy

Learn to fetch crypto data, design strategies, backtest & optimize, then deploy a 24/7 automated trading bot
Created byPython for Finance Mastery
Last updated 9/2025
English

What you'll learn

  • Collect and process real crypto market data directly from exchange APIs, including handling pagination and calculating key indicators.
  • Design and backtest algorithmic trading strategies by building a custom Python backtesting engine and applying professional performance metrics
  • Optimize and manage risk in automated strategies by tuning parameters, adding stop-loss and target-profit logic, and avoiding common curve-fitting pitfalls.
  • Deploy a fully automated trading bot to the cloud—connect to an exchange testnet, run 24/7, and adapt the framework to their own strategies and markets.

Course content

5 sections • 22 lectures • 3h 52m total length

  • Introduction1:02
  • Risk Disclaimer1:29
  • Why build a Crypto Trading Bot?1:26
  • Understanding Crypto Trading Bots1:05
  • From Data to Deployment: Your Bot Roadmap1:30

    Start simple, then scale by building a solid foundation. This roadmap guides you from market data and signals to backtesting, stop loss, take profit, and deployment on Binance testnet.

  • Course Resources & How to Get Help1:02

Requirements

  • Basic Python knowledge – be comfortable with variables, loops, functions and simple data structures (lists, dictionaries).

Description

Build a Fully-Automated Crypto Trading Bot in Python – From Zero to 24/7 Deployment

Learn how professional algorithmic traders design, test, and run crypto strategies—without relying on black-box libraries or expensive tools.
This hands-on course takes you step-by-step from raw market data to a live, cloud-hosted trading bot.

What You’ll Learn

Fetch and Prepare Data

  • Access real-time and historical crypto data through exchange APIs.

  • Handle pagination and calculate key technical indicators to power your strategy.

Backtest the Right Way

  • Discover why plug-and-play backtesting libraries can be dangerous.

  • Build your own backtesting engine from scratch for complete transparency.

  • Include costs, slippage, and commissions for realistic results.

  • Measure performance with professional metrics: Total Return, Sharpe Ratio, Max Drawdown.

Optimize and Control Risk

  • Tune strategy parameters with light and in-depth optimization.

  • Integrate stop-loss and target-profit logic, then optimize those risk controls.

Go Live with Confidence

  • Connect securely to an exchange testnet and place orders programmatically.

  • Package your strategy into an executable Python script ready for production.

  • Deploy your bot to a cloud server for true 24/7 autonomous trading.

Why This Course Stands Out

  • No black boxes – understand every line of code you run.

  • Practical focus – real exchange APIs, real deployment steps.

  • Transferable skills – adapt the framework to any market or strategy.

Prerequisites

  • Basic Python (functions, loops, simple data structures)

  • Basic trading knowledge is helpful but not required

Who this course is for:

  • Python developers or data-science enthusiasts who want to apply their coding skills to real-world trading projects.
  • Aspiring algorithmic or quantitative traders who want to learn how to design, backtest and deploy automated crypto strategies.
  • Crypto investors and hobbyists interested in building bots to test and automate their own trading ideas.
  • Finance or engineering students looking for a practical project that combines programming, trading logic and cloud deployment.

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