Stefan Jansen
1.9K Subscribers
Author, ML for Trading · Founder, Applied AI · Investing since 2013
Stefan Jansen takes you from idea to deployable trading strategy
Stefan is the author of ML for Trading — the book and open-source companion code (20,000+ GitHub stars) that have become a practitioner reference for applying ML to financial markets. The 2026 third edition expands to nine cross-asset case studies, with a foreword by Antonio Gulli, Senior Director, Google.
He maintains the Zipline fork the quant community relies on, and built the six-library stack — data to live — behind the third edition's case studies. Investment partner since 2013, he has built trading platforms and live strategies across asset classes. In 2016 he founded Applied AI, which brings production ML to investment teams and other data-rich verticals. He has taught ML to 110,000+ professionals through DataCamp and General Assembly, incl. at Bloomberg and BlackRock.
Courses
Multi-day, guided programs to get real results
Course11 weeks
ML for Trading: From Research to Production
Conduct rigorous, iterative research across the full trading pipeline, with a working codebase and nine case studies in different markets.
5.0(4)
Course
ML for Trading: Foundations
You finish with a pipeline that runs end to end, and with the evidence to say what it does and does not establish.
View course
Workshops
Single-day, hands-on sprints to practice new skills
Workshop5.5 hours
Engineering a Multi-Agent Forecasting System
Build a multi-agent forecasting system you can audit — in one day.
4.9(8)
·Oct 3Workshop4 hours
Loop Engineering: Reliable Work From Coding Agents
Reliable work from coding agents starts with the loop, not the prompt.
Oct 24
View workshop Workshop4.5 hours
ML for Trading in the Age of AI Agents
Run the whole ML for Trading workflow once, end to end, in a single session.
Oct 10
View workshop Lightning Lessons
Free, interactive sessions to explore new topics
Lightning Lesson30 minutes
How to Be Productive with Coding Agents, Beyond Code
LIVE·Wed, Sep 30, 11:00 AM
Sign up Lightning Lesson30 minutes
How AI Agents Change the ML for Trading Workflow
LIVE·Wed, Oct 7, 11:00 AM
Sign up Lightning Lesson30 minutes
Why Multi-Agent Systems Break, and How To Fix It
LIVE·Wed, Nov 4, 11:00 AM
Sign up Lightning Lesson30 minutes
How to Engineer a Multi-Agent System
WATCH
Watch now Lightning Lesson30 minutes
Managing Your Strategy Research Process
WATCH
Watch now Lightning Lesson30 minutes
Navigate ML for Trading, 3rd Edition
WATCH
Watch now Alumni reviews
This is a highly professional course — in its content, in the standard of the lectures, and in the rigour with which it is delivered. Following Stefan's lessons was a genuine pleasure, and I have rarely come across a course so carefully crafted and so thoroughly prepared down to the last detail. The material is advanced and current, yet it is presented clearly and with a hands-on approach; on top of that, Stefan was always available and extremely generous in going deeper on anything I was curious about.
I would recommend this course to professionals in the financial industry and to students on Master's programmes in Finance or Data Science who want to learn not only the techniques and the models, but also — and perhaps more importantly — the working method. Taking this course felt like stepping into the operations room of a hedge fund, or onto an advanced proprietary trading desk at an investment bank.
Paolo
Cohort 1
risk manager · consultinvest
This was a great course! There is more material in Stefan's book, accompanying GitHub and in this course than there is in many master's degrees. This is definitely high level and not a 101 course. You will get a tremendous amount from this course if you are prepared. Stefan was also always willing to answer emails and answer questions. Highly recommended!
Greg
Cohort 1
CIO · VOFCO, LLC
Stefan’s knowledge of machine learning and quantitative trading is exceptional. He combines rigorous theory with deep real-world experience and explains complex ideas clearly. You will learn a tremendous amount from his practical insights and thoughtful guidance. I highly recommend this course to anyone serious about applying machine learning to financial markets.
Pedram
Cohort 1
Professional practice Associate Professor · Utah State University (Department of Data Analytics and Information Systems)
Excellent course for anyone serious about building practical AI agent systems. Stefan does a great job connecting the concepts behind multi-agent architectures with hands-on engineering and real-world applications. I especially appreciated the focus on building reliable workflows rather than simply experimenting with LLMs. I’m applying what I learned to develop multi-agent systems for complex research and government proposal development, where agents can specialize in research, analysis, writing, compliance, and review—highly recommended for anyone looking to move from using AI assistants to engineering robust agentic systems.
Amir
Cohort 2
CEO · Ocean Reviver Inc.
The course was very well structured and thoughtfully prepared. I particularly appreciated its coverage of current LLM implementation patterns, which made the course highly relevant and practical.
Atsushi
Cohort 2
Machine Learning Engineer · Open Database Associates BV