Stefan Jansen takes you from idea to deployable trading strategy

Excellent course for anyone serious about using coding agents in production. Stefan goes beyond basic prompting to build reliable, repeatable engineering workflows with clear planning, verification, and execution practices. I left with practical techniques I can apply immediately to AI-assisted software development—highly recommended for engineers, technical founders, and engineering leaders.

This is one of those rare courses that sets you in a direction and gives you tools to cut your own path. The entire field is developing extremely rapidly, so I found no better way to leverage your time learning, separating what's permanent from what's transient and walking away with a high quality working prototype than piggy-bagging on the knowledge of experts. If you have been exposed to Stefan's work, you would know: there is no chaff, the code works, your understanding coming out of it is structured and clear. Don't kid yourself, though. You will not walk away an expert programmer of forecasting agents, no will you have a crystal ball. What you will have is a solid, workable scaffolding and a suite of correct tools to work independently in a focused direction. The code itself is worth the cost of the course. Best, VK.

The course offers comprehensive prepared material covering the subject matter in great depth. It helps to come well-prepared, having read the paper and setup the repository based on the thorough instruction provided. I do not believe you can find this information anywhere else right now. Looking forward to syncing up this knowledge base with the third edition of Machine Learning for Trading.

Outstanding session. Stefan delivers a production grade multi-agent forecasting framework with exceptional depth - from ReAct agent loops and calibration techniques to security hardening and cost optimization. The hands-on notebooks and real-world case studies make this immediately applicable to quant trading and research workflows. The emphasis on point in time data, evidence trails, and quality gates reflects real production experience. Highly recommended for anyone building serious AI driven forecasting systems!