Overview
Embark on your journey into the transformative world of AI with the Machine Learning Specialization, a comprehensive online program developed through a pioneering collaboration between DeepLearning.AI and Stanford Online. Dive into the third course of this foundational series, where you will:
- Explore the realm of unsupervised learning, mastering techniques such as clustering and anomaly detection.
- Develop sophisticated recommender systems using both collaborative filtering approaches and content-based deep learning methods.
- Design a cutting-edge deep reinforcement learning model, paving your way to building intelligent systems.
Guided by Andrew Ng, a renowned AI expert with significant contributions at Stanford University, Google Brain, Baidu, and Landing.AI, this Specialization is perfect for beginners eager to understand the fundamentals of machine learning. With a history of ground-breaking research and a dedication to advancing AI, Andrew Ng's teachings are both insightful and inspirational.
The Machine Learning Specialization offers an updated and expanded curriculum based on Andrew’s iconic course that has trained over 4.8 million learners since 2012. With an impressive rating of 4.9 out of 5, this Specialization covers a broad range of topics, including but not limited to supervised learning, unsupervised learning, and best practices hailing from Silicon Valley’s AI and machine learning innovations.
By the end of this program, you will have acquired the essential skills and experiential knowledge to apply machine learning effectively to solve challenging real-world problems. Whether you're aiming to break into AI or advance your career in machine learning, starting with the Machine Learning Specialization on Coursera is a step towards achieving your goals. Join now and be part of the next wave of AI innovation. Categories: Machine Learning Courses, Reinforcement Learning Courses, Unsupervised Learning Courses, Recommender Systems Courses.
Syllabus
Taught by
Andrew Ng, Eddy Shyu, Aarti Bagul and Geoff Ladwig