About this Specialization

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The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. This beginner-friendly program will teach you the fundamentals of machine learning and how to use these techniques to build real-world AI applications. This Specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field. This 3-course Specialization is an updated version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012. It provides a broad introduction to modern machine learning, including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, and more.) By the end of this Specialization, you will have mastered key concepts and gained the practical know-how to quickly and powerfully apply machine learning to challenging real-world problems. If you’re looking to break into AI or build a career in machine learning, the new Machine Learning Specialization is the best place to start.
Shareable Certificate
Earn a Certificate upon completion
100% online courses
Start instantly and learn at your own schedule.
Coursera Labs
Includes hands on learning projects.
Learn more about Coursera Labs External Link
Flexible Schedule
Set and maintain flexible deadlines.
Beginner Level
Approximately 3 months to complete
Suggested pace of 9 hours/week
English
Shareable Certificate
Earn a Certificate upon completion
100% online courses
Start instantly and learn at your own schedule.
Coursera Labs
Includes hands on learning projects.
Learn more about Coursera Labs External Link
Flexible Schedule
Set and maintain flexible deadlines.
Beginner Level
Approximately 3 months to complete
Suggested pace of 9 hours/week
English

How the Specialization Works

Take Courses

A Coursera Specialization is a series of courses that helps you master a skill. To begin, enroll in the Specialization directly, or review its courses and choose the one you'd like to start with. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. It’s okay to complete just one course — you can pause your learning or end your subscription at any time. Visit your learner dashboard to track your course enrollments and your progress.

Hands-on Project

Every Specialization includes a hands-on project. You'll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you'll need to finish each of the other courses before you can start it.

Earn a Certificate

When you finish every course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.

There are 3 Courses in this Specialization

Course1

Course 1

Supervised Machine Learning: Regression and Classification

4.9
stars
5,455 ratings
Course2

Course 2

Advanced Learning Algorithms

4.9
stars
1,243 ratings
Course3

Course 3

Unsupervised Learning, Recommenders, Reinforcement Learning

4.9
stars
578 ratings

Offered by

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DeepLearning.AI

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Stanford University

Frequently Asked Questions

More questions? Visit the Learner Help Center.