Step 1Beginner
Python Trading Fundamentals
Start your algorithmic trading journey. Learn essential libraries, data analysis, and financial chart visualization with Python.
2-3 weeks
6 lessons
Skills You'll Gain
Python BasicspandasNumPyyfinanceMatplotlibmplfinanceJupyterData Analysis
Lessons
1
Python Environment Setup
35 minInstall Python, set up virtual environments, and configure your IDE for algorithmic trading.
Python installvenvVS CodeJupyter
2
Fetching Market Data with yfinance
50 minDownload OHLCV data for stocks, forex, and crypto from Yahoo Finance.
OHLCV dataForex dataCrypto dataReal-time quotes
3
Data Analysis with pandas
45 minMaster DataFrames for financial data manipulation, rolling windows, and trading signal generation.
DataFramesTime seriesRolling windowsResampling
4
Numerical Computing with NumPy
40 minUse NumPy for fast vectorized computations, statistics, and performance optimization.
ArraysVectorizationStatisticsLinear algebra
5
Financial Chart Visualization
30 minCreate professional candlestick charts with indicators and volume overlays using mplfinance.
Candlestick chartsVolume overlayCustom styles
6
Essential Trading Libraries
25 minComplete overview of the Python trading ecosystem — data, backtesting, ML, and broker APIs.
Library ecosystemChoosing toolsBest practices
Next Step
After completing the fundamentals, move on to backtesting frameworks and advanced analysis.
Step 2: Backtesting & Analysis