Andrew Ng

Andrew Ng is Co-founder of Coursera, and an Adjunct Professor of Computer Science at Stanford University. His machine learning course is the MOOC that had led to the founding of Coursera!

In 2011, he led the development of Stanford University’s main MOOC (Massive Open Online Courses) platform and also taught an online Machine Learning class to over 100,000 students, thus helping launch the MOOC movement and also leading to the founding of Coursera.

Ng also works on machine learning, with an emphasis on deep learning. He had founded and led the “Google Brain” project, which developed massive-scale deep learning algorithms. This resulted in the famous “Google cat” result, in which a massive neural network with 1 billion parameters learned from unlabeled YouTube videos to detect cats. Until recently, he led Baidu's ~1300 person AI Group, which developed technologies in deep learning, speech, computer vision, NLP, and other areas.

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Building Systems with the ChatGPT API (Coursera) Coursera
DeepLearning.AI

Building Systems with the ChatGPT API (Coursera)

Discover how to automate intricate processes and elevate your development skills with 'Building Systems with the ChatGPT API'. This course will guide you through chaining calls to a powerful language model, enabling you to create sophisticated systems that streamline workflows and boost productivity. Perfect for developers looking to innovate and excel in their projects.

Sep 21st 2026
1 Week
Understanding and Applying Text Embeddings (Coursera) Coursera
DeepLearning.AI

Understanding and Applying Text Embeddings (Coursera)

Dive into the world of text embeddings with our expert-led course. Discover how to transform textual data into numerical forms using the Vertex AI Text-Embeddings API. Enhance search algorithms, refine product recommendations, and personalize user experiences by mastering this essential skill in natural language processing.

Sep 14th 2026
1 Week
Machine Learning (Coursera) Coursera
Stanford University

Machine Learning (Coursera)

Discover the fascinating world of Machine Learning with this in-depth online course offered by Coursera. Designed for those new to the field, this course will guide you through the fundamentals of making computers 'learn' without being explicitly programmed. From understanding the science behind machine learning to applying effective techniques and gaining hands-on experience, this course is your gateway to mastering a technology that's revolutionizing industries.

Sep 7th 2026
5-12 Weeks
AI For Everyone (Coursera) Coursera
DeepLearning.AI

AI For Everyone (Coursera)

Unlock the potential of Artificial Intelligence (AI) with our beginner-friendly course, 'AI For Everyone'. This comprehensive guide is tailored for individuals from all backgrounds who wish to harness the power of AI in their professional lives. Whether you're a marketer, manager, or simply curious about how AI can benefit your organization, this course will equip you with the foundational knowledge needed to start leveraging AI effectively.

Sep 7th 2026
4 Weeks
Advanced Learning Algorithms (Coursera) Coursera
Stanford University,DeepLearning.AI

Advanced Learning Algorithms (Coursera)

Expand your knowledge in machine learning by diving into 'Advanced Learning Algorithms'. This course will guide you through building and training complex neural networks using TensorFlow for effective multi-class classification tasks. You'll also learn best practices for developing machine learning models that generalize well to real-world data and scenarios, as well as explore decision trees and ensemble methods like random forests and boosted trees.

Sep 7th 2026
4 Weeks
Unsupervised Learning, Recommenders, Reinforcement Learning (Coursera) Coursera
Stanford University,DeepLearning.AI

Unsupervised Learning, Recommenders, Reinforcement Learning (Coursera)

Dive into the world of advanced machine learning with our 'Unsupervised Learning, Recommenders, Reinforcement Learning' course. This comprehensive program will equip you with essential skills in unsupervised learning techniques like clustering and anomaly detection, as well as cutting-edge approaches to building effective recommender systems and implementing deep reinforcement learning models.

Sep 7th 2026
3 Weeks
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