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University of California, San Diego

Machine Learning Fundamentals

University of California, San Diego via edX


Do you want to build systems that learn from experience? Or exploit data to create simple predictive models of the world?

In this course, part of the Data Science MicroMasters program, you will learn a variety of supervised and unsupervised learning algorithms, and the theory behind those algorithms.

Using real-world case studies, you will learn how to classify images, identify salient topics in a corpus of documents, partition people according to personality profiles, and automatically capture the semantic structure of words and use it to categorize documents.

Armed with the knowledge from this course, you will be able to analyze many different types of data and to build descriptive and predictive models.

All programming examples and assignments will be in Python, using Jupyter notebooks.

Taught by

Sanjoy Dasgupta


3.9 rating, based on 8 Class Central reviews

4 rating at edX based on 13 ratings

Start your review of Machine Learning Fundamentals

  • Anonymous
    This is the second course from UCSanDiegoX (early 2018 run) that breaks the enrollment clause stating "Audit this course for free and have complete access to all the course material, activities, tests, and forums". There was no final exam for Audit…
  • Anonymous
    I have a few things to say about this course. Firstly, the lectures content is very good as the main concepts of ML models are explained well by Sanjoy Dasgupta. However, he misses on explaining the F1-score, precision and recall metrics which are…
  • Profile image for Luiz Cunha
    Luiz Cunha
    I agree with others positive comments regarding this course. I have taken a few popular ML courses. This is probably the best one:
    Instructor is top notch, good material, good videos and very clear explanations.
    There are lots of exercises.
    The only small objection is regarding the python notebooks and the related exercises: the notebooks quaility could have been better (wonder if the person that wrote them has any good CS experience); and the notebook question/exercises could have been better: either too easy, or requiring a touch too much unguided dev: would have enjoyed it more if it was more like in Andrew Ng notebooks in his popular Machine Learning MOOC.
  • Anonymous
    I wouldn't waste time on this course. There are many books in machine learning.

    Four of my favorites are:

    _ Machine Learning for .NET Developers: Build Smarter Applications by Teaching Them to Learn from Data_ by Mathias Brandenwinder

    _Machine Learning: An Algorithmic Perspective_ by Stephen Marsland

    _MATLAB Machine Learning_ by Michael Paluszek

    _Machine Learning Hands-on for Developers and Technical Professionals_ by Jason Bell

    (I could expand this list with about forty more entries.)

    Jim Collier

    Orange County, CA

    Christmas Day, 2020
  • Profile image for Prakash L
    Prakash L
    Overall the course is great and the instructor is awesome. Machine learning is fascinating and I now feel like I have a good foundation. A few minor comments: some of the projects had too much helper code where the student only needed to fill in a portion of the algorithm. I would have preferred to have worked through more of the code. Also, there were a few times when the slides didn't contain the complete equations so it was difficult to piece it all together when writing the code. Lastly, I wish that there was more coverage on vectorized solutions for the algorithms.
  • Profile image for ömer Yalçın
    ömer Yalçın
    I think this course is one of most usefull machine learning courses at internet . Teacher is really good , there are enough math and code exercises
  • Pra
    I audited this course. Professor Sanjoy Dasgupta you are a hero! Such a great teaching style. This is by far the best ML course in internet.
  • Anonymous
    Fantastic course that teaches you the actual "fundamentals" of machine learning, one of the best machine learning courses on a MOOC. However there is a prerequisite that you must also complete the 2 courses (out of a set of 4 courses for the MicroMasters) prior first to get the best out of it!

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