# Build Your Own Crypto Trading Bot – Course Repository

Welcome to the private repository for the **"Build Your Own Crypto Trading Bot – Hands-On Course with Alex"** by QuantJourney.

This repository contains materials, templates, and code samples used during the 6 live sessions held in June 2025.

> ⚠️ This repository is for registered participants only.

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## Content Overview

**Session 1: Foundations & Data Structures**
- Set up Python, IDE, and required libraries
- Pandas basics for financial time series
- Understanding OHLCV format
- Create your first crypto DataFrame with sample data

**Session 2: Data Acquisition & Exchange Connectivity**
- WebSocket basics for real-time crypto feeds (Binance focus)
- Fail-safe reconnection logic and error handling
- Logging basics for live systems
- Build tools: order flow scanner, liquidation monitor, funding rate tracker

**Session 3: Data Processing & Technical Analysis**
- API access using CCXT
- Handle rate limits and API error scenarios
- Reconnect & retry mechanisms
- Use pandas-ta to compute SMA, EMA, RSI
- Create your own indicator pipeline

**Session 4: Strategy Development & Backtesting**
- Overview of strategy types (trend, mean reversion)
- Backtesting with `backtesting.py`
- Compute Sharpe ratio, drawdown, profit factor
- Add position sizing, SL/TP, and walk-forward logic
- Adjust for fees, slippage, and latency

**Session 5: Bot Architecture & Implementation**
- Bot system design: event-driven vs loop-based
- Core components: order manager, position tracker, error handler
- Risk constraints: daily limits, max size
- Logging & monitoring structure
- Write the engine core for your bot

**Session 6: Live Trading & Deployment**
- API keys and secure credential handling
- Deployment targets: local, VPS, cloud (e.g., Hetzner)
- Running 24/7: restart logic, alerting
- Final bot launch + testing in production
- Send alerts via Telegram or email

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## 🤖 AI-Enhanced Trading
Bonus section:
- Use ChatGPT/Claude for strategy suggestions
- Integrate AI-based filters or signal generation
- Let LLMs help you refactor and extend your logic

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## 📁 Repository Structure

```text
/Session_01/      # Foundations & DataFrame Handling
/Session_02/      # WebSockets & Real-Time Feed Tools
/Session_03/      # Indicators & Analysis
/Session_04/      # Backtesting + Strategy Logic
/Session_05/      # Trading Bot Core Engine
/Session_06/      # Live Deployment and Monitoring
/templates/     # Starter and final bot code
/utils/         # Helper scripts for logging, reconnection, etc.
README.md       # You are here
```

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## 🛠 Requirements
- Python 3.10+
- Install dependencies per session in each folder or via a top-level `requirements.txt` (provided)

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## 📫 Support
You can reach Alex directly at [alex@quantjourney.pro](mailto:alex@quantjourney.pro) for post-course support (1 week included).

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## ⚠️ Disclaimer
This project is for **educational use only**. No financial advice. Always trade with caution and use proper risk management.

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Happy coding – and trade smart.

QuantJourney Team

