Algorithmic Trading with Python (Udemy.com)
Build, Backtest & Optimize Trading Strategies with Real Data – Momentum, VIX, Machine Learning & Portfolio Optimization
Created by: Python for Finance Mastery
Last updated March 2026
What you will learn
- Learn how to code in Python from scratch
- Be a PRO in Data Analysis in specific Financial Data
- Build and Backtest Trading Strategies with Python
- Understand and Optimize the Return and Risk profile of your Portfolio
- Compare stocks and Portfolio in terms of their Sharpe ratio
- Have an outstanding technical skillset to apply for a quant job in a financial institution or data based company
- Be able to perform in depth Investment Analysis
- Solve real-world problems using Python
- Visualize your data in interactive Dashboards
- Learn about best practices and relevant practice advice working with financial data
- Be able to compare stocks
- Understand the difference between Log returns and returns
- Optimize weights by using the concept of the Efficient Frontier
- Leverage Algebra concepts to do powerful calculations
How it compares
Against the other 376 rated Udemy courses in Finance & Accounting on CourseDuck:
- Rating4.4 out of 5higher than 28% of them
- Reviews245#249 of 377 by number of reviews
- Length9 hourslonger than 70% of them
- Last updatedMarch 2026more recently than 68% of them
Course Description
Build Real Algorithmic Trading Strategies with Python — From Data to Backtesting and Optimization
This course teaches you how to design, implement, and evaluate real trading strategies using Python.
Instead of learning isolated concepts, you’ll work through complete, practical workflows used in quantitative finance — from pulling market data to building and optimizing trading systems.
By the end of this course, you will be able to:
• Build and backtest momentum and volatility-based trading strategies
• Work with real financial time series data using Pandas
• Create fully vectorized backtests (fast and scalable)
• Apply machine learning models to financial data
• Optimize portfolios using modern risk/return techniques
• Build interactive dashboards to analyze performance
• Store and manage financial data using SQL
What Makes This Course Different?
Most courses teach Python concepts in isolation. This course teaches you how to apply them in a consistent, real-world framework:
→ Data → Signal → Strategy → Backtest → Optimization
Every project builds on this pipeline, so you don’t just learn tools — you learn how to combine them into complete systems.
Real Projects You’ll Build:
• Cross-sectional and time-series momentum strategies
• A VIX-based trading strategy inspired by institutional research
• A machine learning model for market prediction
• Portfolio optimization using the Sharpe Ratio
• A Streamlit dashboard for analyzing market performance
• A financial database using Python and SQL
Who This Course Is For:
• Beginners who want to learn Python with a clear, practical goal
• Aspiring quants and analysts
• Traders who want to automate and backtest strategies
• Anyone interested in applying data science to financial markets
No fluff, no toy examples — just practical, real-world projects that show you how algorithmic trading and quantitative analysis actually work.
Start building your own trading strategies with Python today.
Instructor Details
- 4.4 Rating
245 Reviews
Python for Finance Mastery
I am a full-time professional at a leading trading firm, working daily with real financial markets, real capital, and real data. My work sits at the intersection of quantitative finance, Python, and data science — not theory, but production-level applications used in practice.
I hold two university degrees and have spent years applying Python to market data, derivatives, and systematic analysis. Alongside my professional work, I teach these skills to a global audience of over 125,000+ subscribers on YouTube, where I am known for turning complex financial concepts into clear, practical, and actionable frameworks.
My courses are designed for people who want real skills, not academic fluff. You will learn how Python is actually used in finance — from data analysis and modeling to strategy research and decision-making — with a strong focus on clarity, intuition, and hands-on implementation.
Unlike many instructors, I don’t teach finance about Python — I teach Python as it is used by professionals in finance. Everything you learn is grounded in real-world workflows, realistic assumptions, and industry-relevant examples.
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Reviews
By Al Mercado on 1/6/2026
It reduces the topics to the underlying mathematics that define it. A textbook was referenced for portfolio management that I wish could be downloaded from the resources provided
By Ricardo Neves on 11/23/2025
I like the way everything is explained. The only thing I noticed, was that most of the more complex videos already exist in the Algovibes Youtube channel. Anyway the content is very good, thanks!
By Antonis Patinios on 2/6/2025
Great course, some areas seem to be a bit more advanced than others so I skipped over them for the time being. Overall, happy to have learned a few basics and following the less intense projects were especially helpful.
By Lee Yu Jie on 6/4/2024
As someone with a degree in quantitative finance and is a Java software engineer with some experience in Python, I find this course very disappointing. The creator did not put in effort to localize the content to the Udemy platform - this is literally a collection of youtube videos. The course is peppered with phrases like "I will link the video somewhere", or "you can find this in the description", or "you can leave a comment below" etc. I've also been to the youtube channel. The course content is unfocused. It begins with a very introductory overview of Python programming, seemingly for viewers with no experience in Python or programming. It then jumps to libraries for intermediate-level programmers. The same is true Finance concepts - you are taught how to calculate percentage change, then suddenly logistic regression is used. All these in 9 hours of content. I don't recommend this course for anyone who wants to learn python programming. I also don't recommend this course for anyone who wants to learn data science, or finance, or trading strategies.
By Ankit Goyal on 4/2/2024
I had preconceptions that python would be difficult to understand as I come from Non-Tech background and using it for finance will be more difficult to understand. I found difficulty in understanding it for the first time, yet, but still loved the course and would go all over again to invest my time in the course to understand it more properly and implement it.
By Hadwan Ladaa on 2/27/2024
very good course despite some parts of this course are higher my level -related to sql (it is my problem), I can describe this course with statements: great course professional instructor clear & easy explanation quick reply for the questions huge thanks to you Algovibes
By Walter Gantenbein on 2/16/2024
If you are interested in Python and finance, this course is an absolute must! Clear and simple explanation of the material and scripts. Elegant solutions to the problems. I look forward to further courses.
By Gianfranco Silvestri on 8/2/2023
I like: 1. The quality of code: simple and effective, easy to understand and to run 2. The quality of explanation: clear and immediate understanding of the focal point Some doubts about: 1. The contents: I hoped the training could be oriented more toward real time script, able to perform analisys and entries on a data feed.
By Daniel Punton on 7/14/2023
Moving quickly and clearly. I already know some python so this is a lot less head hurting than being shown every example of malformed variable name.
By Dennie Harms on 6/20/2023
Very good course, explained step by step. Even absolute beginners are able to do a lot with these powerful tools afterwards. I was used to program in other languages beforehand, also trading strategies and robots, but no experience in python. The possibility to do backtests over 1000s of assets at the same time in good quality with free tools fascinated me. The course covers so many important points in a reasonable order, relatively easy to follow and gain a lot of knowledge to create own backtests, dashboards, databases, etc.
Quality Score
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Overall Score : 88 / 100






