Tue, Sep 29, 2026
7:00 AM UTC (1 hour)
Virtual (Zoom)
Free to join
Go deeper with a course

Tue, Sep 29, 2026
7:00 AM UTC (1 hour)
Virtual (Zoom)
Free to join
447 students
Go deeper with a course

What you'll learn
Emerging AI Stack Architecture
Building Agent Harnesses
Production Deployment Trade-Offs
Future-Proof Engineering Practices
Why this topic matters
You'll learn from
Hugo Bowne-Anderson
AI Builder/Educator (6 Million Students)
Hugo Bowne-Anderson is an independent data & AI consultant with extensive experience in the tech industry. He has advised and taught teams building AI-powered systems, including engineers from Netflix, Meta, & Amazon. He is the host of the industry Vanishing Gradients, where he explores cutting-edge developments in data science and artificial intelligence, & has written for publications such as Harvard Business Review & VentureBeat. Previously, Hugo served as Head of Developer Relations at Outerbounds & held roles at Coiled & DataCamp, where his work in data science education reached over 6 million learners. He has taught at Yale University, Cold Spring Harbor Laboratory, and conferences like SciPy and PyCon, & is a passionate advocate for democratizing AI skills and open-source tools.
Alexey Grigorev
Principal Data Scientist | Book Author | Instructor to 100k+ Students World-Wide
Alexey Grigorev is the founder of DataTalks.Club and the creator of the popular Zoomcamp series. With 15 years of experience in software engineering and over 12 years in machine learning, he has built and deployed large-scale ML systems at companies like OLX Group and Simplaex.
An advocate for practical, hands-on education, Alexey has taught over 100,000 students, focusing on a code-first approach to help learners build real-world skills.
In the past, he was an active participant in data science competitions. A Kaggle Master, Alexey has achieved top rankings in several challenges, including 1st place in the NIPS'17 Criteo Challenge and 2nd place in the WSDM Cup 2017: Vandalism Detection.
He is also the author of several technical books, including the widely read Machine Learning Bookcamp.
