Udemy

Become a Quant: Algorithmic Trading with Python and AI

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  • 5,739 Students
  • Updated 3/2026
4.7
(739 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
16 Hour(s) 47 Minute(s)
Language
English
Taught by
Cheng Li | Quant Developer and Instructor
Rating
4.7
(739 Ratings)
1 views

Course Overview

Become a Quant: Algorithmic Trading with Python and AI

Build, Backtest and Live-Trade Stocks, Options, Futures, Forex, Crypto Trading Bots on QuantConnect — Certified Partner

Welcome to Become a Quant: Algorithmic Trading with Python and AI!


Why this course:

  • Start Instantly, Even with Zero Coding Skills — Skip the steep learning curve and build trading bots from scratch—no prior programming experience needed

  • Everything You Need in One Place — Build trading bots for stocks, options, futures, forex, and crypto—no need to piece together multiple resources

  • Learn from a Trusted Quant Developer — Get expert guidance from a Top-Rated Fiverr Pro Quant Developer trusted by professionals from Citi, Credit Suisse, and top hedge funds

  • Save Time with Insider Insights — Avoid rookie mistakes and accelerate your progress with tips from a Certified QuantConnect Integration Partner

  • Build Smarter and Faster with AI — Use AI as your coding co-pilot to develop powerful features with ease

  • Trade Smarter with Machine Learning — Forecast prices using real-world machine learning models like Random Forest and XGBoost—gain a data-driven edge

  • From Backtesting to Live Trading: Learn the required resources for live trading and how to export real-world trading signals


What you'll build:

  • Stock Trading Bot Foundation Build stock trading bots to master the core algorithmic trading framework—so you can expand to other asset classes

  • Advanced Asset-Class Trading Bots — Build complex trading bots for options, futures, forex, and crypto—so you can handle asset-specific mechanics across markets

  • Machine-Learning Modules — Train and deploy Random Forest and XGBoost models—so you generate more powerful, data-driven signals for your trading bot

  • Pro-Grade Extras — Build market scanners, perform financial-statement and sentiment analysis, and explore additional cutting-edge features for algorithmic trading


What you'll learn:

  • Master Python Essentials — Skip the fluff; learn only the syntax and libraries needed to build trading bots

  • Code Faster with AI — Leverage an AI copilot to add advanced features in minutes

  • Deploy ML Forecasts — Engineer and train Random Forest and XGBoost models, then integrate predictions into your trading bot

  • Complete Data Management — Stream data feeds, design data structures, and tap into alternative data sources for algorithmic trading

  • Complete Trading Logic — Master portfolio management, risk management, and scheduled events for end-to-end trading automation

  • Backtest with Depth — Access decades of historical data and pro-level performance reports in QuantConnect

  • Options and Futures Logistics — Manage expiries, Greeks, and margin to control risk effectively

  • Craft an Indicator Playbook — Combine multiple indicators for robust entry and exit signals

  • Live-Trading Operations Required resources, signal export methods, and performance considerations for real markets


What you'll get:

  • Practice Actively — Quizzes and coding exercises lock concepts in place

  • Enjoy Lifetime Access — Buy once, learn forever!

  • Grab the Source — Download all slides and full example code files

  • Zero-Risk Guarantee — 30-day money-back promise


Still thinking?

  • Watch Day 2's lecture for free, see a successful backtest, and judge for yourself!


Enroll now to start building your very own trading bots with Python, AI, machine learning, and QuantConnect—today!

Course Content

  • 69 section(s)
  • 64 lecture(s)
  • Section 1 Day 1 - Course Introduction (2026)
  • Section 2 Day 2 - Python Essentials (2026)
  • Section 3 Day 3 - Python Essentials (2026)
  • Section 4 Day 4 - Python Essentials (2026)
  • Section 5 Day 5 - Python Essentials (2026)
  • Section 6 Day 5 - Python Essentials (2025)
  • Section 7 Day 6 - Python Essentials (2025)
  • Section 8 Day 7 - Python Essentials (2025)
  • Section 9 Day 8 - Python Essentials (2025)
  • Section 10 Day 9 - Python Essentials (2025)
  • Section 11 Day 10 - Python Essentials (2025)
  • Section 12 Day 11 - Python Essentials (2025)
  • Section 13 Day 12 - Python Essentials (2025)
  • Section 14 Day 13 - Python Essentials (2025)
  • Section 15 Day 14 - Python Essentials (2025)
  • Section 16 Day 15 - Python Essentials (2025)
  • Section 17 Day 16 - Python Essentials (2025)
  • Section 18 Day 17 - Python Essentials (2025)
  • Section 19 Day 18 - Python Essentials (2025)
  • Section 20 Day 19 - Python Essentials (2025)
  • Section 21 Day 20 - Python Essentials (2025)
  • Section 22 Day 21 - Python Essentials (2025)
  • Section 23 Day 22 - Python Essentials (2025)
  • Section 24 Day 23 - Python Essentials (2025)
  • Section 25 Day 24 - Python Essentials (2025)
  • Section 26 Day 25 - QuantConnect Essentials (2025)
  • Section 27 Day 26 - QuantConnect Essentials (2025)
  • Section 28 Day 27 - QuantConnect Essentials (2025)
  • Section 29 Day 28 - QuantConnect Essentials (2025)
  • Section 30 Day 29 - QuantConnect Essentials (2025)
  • Section 31 Day 30 - QuantConnect Essentials (2025)
  • Section 32 Day 31 - QuantConnect Essentials (2025)
  • Section 33 Day 32 - QuantConnect Essentials (2025)
  • Section 34 Day 33 - QuantConnect Essentials (2025)
  • Section 35 Day 34 - QuantConnect Essentials (2025)
  • Section 36 Day 35 - QuantConnect Essentials (2025)
  • Section 37 Day 36 - QuantConnect Essentials (2025)
  • Section 38 Day 37 - QuantConnect Essentials (2025)
  • Section 39 Day 38 - QuantConnect Essentials (2025)
  • Section 40 Day 39 - QuantConnect Essentials (2025)
  • Section 41 Day 40 - QuantConnect Essentials (2025)
  • Section 42 Day 41 - QuantConnect Essentials (2025)
  • Section 43 Day 42 - QuantConnect Essentials (2025)
  • Section 44 Day 43 - QuantConnect Essentials (2025)
  • Section 45 Day 44 - QuantConnect Essentials (2025)
  • Section 46 Day 45 - QuantConnect Essentials (2025)
  • Section 47 Day 46 - QuantConnect Essentials (2025)
  • Section 48 Day 47 - QuantConnect Essentials (2025)
  • Section 49 Day 48 - QuantConnect Essentials (2025)
  • Section 50 Day 49 - QuantConnect Essentials (2025)
  • Section 51 Day 50 - QuantConnect Essentials (2025)
  • Section 52 Day 51 - Complicated Asset Classes (2025)
  • Section 53 Day 52 - Complicated Asset Classes (2025)
  • Section 54 Day 53 - Complicated Asset Classes (2025)
  • Section 55 Day 54 - Complicated Asset Classes (2025)
  • Section 56 Day 55 - Complicated Asset Classes (2025)
  • Section 57 Day 56 - Complicated Asset Classes (2025)
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  • Section 60 Day 59 - Complicated Asset Classes (2025)
  • Section 61 Day 60 - Complicated Asset Classes (2025)
  • Section 62 Day 61 - Complicated Asset Classes (2025)
  • Section 63 Day 62 - Complicated Asset Classes (2025)
  • Section 64 Day 63 - Complicated Asset Classes (2025)
  • Section 65 Day 64 - Complicated Asset Classes (2025)
  • Section 66 Day 65 - Complicated Asset Classes (2025)
  • Section 67 Day 66 - Complicated Asset Classes (2025)
  • Section 68 Day 67 - Complicated Asset Classes (2025)
  • Section 69 Day 68 - Complicated Asset Classes (2025)

What You’ll Learn

  • Multi-Asset: Build trading bots for stocks, options, futures, forex, and crypto!, Machine Learning: Build Random Forest and XGBoost models to analyze market data and integrate them into your trading bots!, Algorithm Structure: Learn every component of a trading bot from position sizing and risk management to order handling!, Generative AI: Accelerate algorithm development and create advanced functionalities using AI!, Complex Asset Classes: Learn contract expiry management for options and futures, plus learn to handle options Greeks!, Sophisticated Functionalities: Learn to code advanced tools like market scanners, news sentiment analysis, and scheduled events!, Live-Trading Deployment: Learn to deploy, monitor, and manage trading bots in live markets!, Backtesting: Learn to backtest trading strategies using real-world historical market data!


Reviews

  • R
    R S
    1.0

    a very dull and not a practical course. The choice of code execution platform is very poor, and explanations are unnecessarily long. The structuring of the code is very poor. Why is it structured day 1, day 2, etc.? It should be structured and foldered based on the subject/content or topic.

  • C
    Chris Lee
    5.0

    5 stars for the succinct and clear explanation of the course contents.

  • C
    Caleb
    5.0

    The step by step guide is awesome. slow and steady. clear,audible and accurate visualization.

  • J
    Jonathan Arbat
    5.0

    Sehr guter Kurs, gut strukturiert aufgebaut und auch für mich als Nicht-Muttersprachler ausgezeichnet zu verstehen.

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