Created by:   Stanford University

  • Andrew Ng

    Taught by:    Andrew Ng, Associate Professor, Stanford University; Chief Scientist, Baidu; Chairman and Co-founder, Coursera


Language
English, Subtitles: Spanish, Japanese, Chinese (Simplified)
How To PassPass all graded assignments to complete the course.
User Ratings
4.9 stars
Average User Rating 4.9See what learners said
Syllabus

FAQs

When will I have access to the lectures and assignments?

What if I need additional time to complete the course?

What will I get if I pay for this course?

Can I take this course for free?

What is the refund policy?

Is financial aid available?

How It Works
Coursework
Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

Help from Your Peers
Help from Your Peers

Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.

Certificates
Certificates

Earn official recognition for your work, and share your success with friends, colleagues, and employers.

Creators
Stanford University
The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States.
Ratings and Reviews
Rated 4.9 out of 5 of 28,147 ratings

Very good introduction into the field of machine learning, its various algorithms and use cases. Only point of criticism would be that the level is sometimes a little lower than expected. The pace of the lecture could, in my opinion, be a little faster as I found myself skipping through the videos from time to time hopping over the repetitions. Having said that, it's perfect for everyone without a mathematics background!

The exercises were very good fun and very well managed through the available material, resources and the discussion forum. At the end of the course one - me anyway - wishes to go back to uni and start studying computer science.

I think this was a great course. It goes through high-level concepts as well as digs down into implementation of common algorithms. Professor Ng explains concepts well enough for a novice to easily follow. Would recommend this course to anyone looking for a primer on machine learning.

A great introductory course that is designed such that you don't need a mathematical background in order to understand the concepts. Due to its attempt to maximise accessibility, most concepts are not mathematically motivated, meaning that a person serious about pursuing this as a career will need to do a subsequent course that is more mathematically rigorous. However, it does a great job of building intuition about the algorithms and is a solid base to build on.

Excelente!