Python Crypto Trading Bot: Build, Backtest & Deploy

Python加密货币交易机器人全流程实战

学习从交易所获取数据、设计策略、回测优化到部署24/7自动化交易机器人的完整流程。中级课程，涵盖Python回测引擎与风险管理，适合有基础Python知识的开发者。

Published 9/2025
Created by Python for Finance Mastery
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 22 Lectures ( 3h 54m ) | Size: 1.75 GB

Learn to fetch crypto data, design strategies, backtest & optimize, then deploy a 24/7 automated trading bot

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.

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 DeploymentLearn 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 LearnFetch and Prepare DataAccess real-time and historical crypto data through exchange APIs.Handle pagination and calculate key technical indicators to power your strategy.Backtest the Right WayDiscover 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 RiskTune strategy parameters with light and in-depth optimization.Integrate stop-loss and target-profit logic, then optimize those risk controls.Go Live with ConfidenceConnect 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 OutNo 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.PrerequisitesBasic Python (functions, loops, simple data structures)Basic trading knowledge is helpful but not required