Learn efficiently through live, project-based courses.

All courses
Data Science
Analytics Engineering
Machine Learning
October 10, 2022

Deep Learning Essentials

Kevin Wu
PhD at Stanford; formerly at Waymo, Microsoft
Eric Wu
PhD at Stanford, formerly at Google
October 24, 2022

Search with Machine Learning

Grant Ingersoll
Former CTO at Wikimedia
Daniel Tunkelang
Machine Learning Consultant
November 1, 2022

Personalized Recommendations at Scale

Rishabh Mehrotra
Director of Machine Learning at ShareChat
November 7, 2022

Production Deployment with Kubernetes

Samir Sen
Founder & CEO, Flair Labs
November 14, 2022

Data Centric Deep Learning

Andrew Maas
Senior Manager at Apple and Instructor at Stanford
Mike Wu
PhD Scholar at Stanford
January 2, 2023

Applied Machine Learning

Andrew Maas
Senior Manager at Apple and Instructor at Stanford University
Julie Kallini (co-instructor)
Software Engineer at Meta
January 2, 2023

MLOps: From Models to Production

Nihit Desai
CTO of Refuel.AI (ex-Facebook, Stanford)
January 9, 2023

Natural Language Processing

Sourabh Bajaj
former Engineering Manager at Neeva
Kaushik Rangadurai
Software Engineer at Meta
January 23, 2023

Interpreting Machine Learning Models

Nazneen Rajani
Robustness Research Lead at Hugging Face
March 20, 2023

Building End-to-End Vision Applications

Abubakar Abid
Machine Learning Team Lead at Hugging Face

Career Tracks

Gain expertise with tracks, a collection of courses curated and taught by industry experts.


Acquire the foundational skills you need to be an effective search engineer in this 6 week track, including how to integrate machine learning and natural language processing techniques into search engines.

Analytics Engineering

Acquire the skills required for a career in analytics engineering, including the foundational tools of SQL, Python, and dbt used to organize, transform, and retrieve information for modeling and insights.

Machine Learning Foundations

Gain the skills you need to become an effective machine learning engineer in this 3-course track, with applied machine learning, deep learning, deployment of machine learning projects, and more.

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