Algorithmic Trading

Automate trading strategies. Master quantitative analysis, backtesting frameworks, and execution algorithms using Python and Pandas.

Algorithmic trading removes emotion from investing. This advanced course teaches you to design, backtest, and deploy automated trading strategies. You will learn to process financial time-series data using Pandas, calculate technical indicators (RSI, MACD), and implement Mean Reversion and Momentum strategies. We cover execution algorithms to minimize slippage and connect to broker APIs like Interactive Brokers or Alpaca for live trading.

✅ 100% Free & Lifetime Access

⏱️ 5-Minute Lessons (Bite-sized learning)

🚀 21-Lesson Path (Independent modules)

📱 Mobile Friendly (Learn anywhere)

Quants

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Secure Enrollment via SSL

Complete Course Syllabus

1

Market Data

Fetching and cleaning OHLCV data from APIs.
2

Strategy Logic

Coding simple moving average crossovers.
3

Backtesting

Simulating performance over historical data.
4

Risk Management

Calculating Sharpe Ratio and Max Drawdown.
5

Live Execution

Connecting to a paper trading account.

Estimated completion time: 21 lessons • Self-paced learning • Lifetime access

Career Outlook

Estimated Salary

$150k - $300k

Career Paths

Quantitative Developer $160k-$250k

Algorithmic Trader $150k-$300k+

Financial Data Scientist $140k-$200k

What You Will Learn

Design and backtest automated trading strategies using Python

Process financial time-series data with Pandas and NumPy

Implement Mean Reversion and Momentum trading logic

Connect to broker APIs for live trade execution

Manage risk using position sizing and stop-loss algorithms

Skills You Will Gain

Python Pandas Backtesting Financial APIs Risk Management

Who Is This For

Quant Developers

Traders

Data Scientists

Prerequisites

Python Proficiency

Finance Basics