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Algorithmic Stock Trading and Equity Investing with Python

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Last updated on October 21, 2026 6:38 pm

Algorithmic Stock Trading and Equity Investing with Python

★★★★★
$4,499.00
$699.00
 in stock
as of October 21, 2026 6:38 pm

Interactive Brokers (IBKR) for Algorithmic Trading & Portfolio Investing | Stock Market Analysis, ETF Trading & Theory

Created by: Alexander Hagmann
Data Scientist | Finance Professional | Entrepreneur
Rating:4.62 (394reviews)     6607students enrolled

What Will I Learn?

  • Algorithmic Stock Trading with Python and the Interactive Brokers (IBKR) API
  • Automated ETF & Equity Portfolio Investing
  • Passive (ETF), Semi-Active and Active Investing
  • Stock Trading Strategies with multiple Tickers
  • Equity Portfolio Optimization, Management & Rebalancing
  • Backtesting and Implementation of Trading & Investment Strategies
  • Technical Analysis and Indicators
  • Equity Valuation Methods (DDM and Multiples)
  • Fundamental Analysis
  • Stock Indices and Index Tracking/Replication
  • How to measure, benchmark & improve the Performance of your Equity Portfolio
  • Loading and analysing Stock Data from (free) Web Sources
  • API Trading with Interactive Brokers
  • Python Basics & Numpy, Pandas, Matplotlib
  • Truly Data-driven Trading and Investing
  • Asset-Pricing Models (CAPM)
  • Black-Litterman Model

Requirements

  • No Python experience needed. This course provides a Python Crash Course.
  • No Finance/Investment knowledge required. You will learn everything you need to know.
  • A desktop computer (Windows, Mac, or Linux) capable of storing and running Anaconda. The course will walk you through installing the necessary free software.
  • An internet connection capable of streaming HD videos.
  • Some high school level math skills would be great (not mandatory, but it helps).

Target audience

  • Beginners who want to start with Stocks/equities and want to do it right straight way (avoiding common mistakes).
  • Stock Traders and Investors who want to professionalize and automate their Business.
  • Finance & Investment Professionals who want to step into Data-driven Finance.
  • Data Scientists and Machine Learning Professionals with an interest in Investing into Stocks/Equities.

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