Machine Learning Foundations: A Case Study Approach Review

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   I just completed another certification and wanted to give my opinion on the Coursera course,"Machine Learning Foundations: A Case Study Approach". This course is the starting course of a four part program provided by the University of Washington in Coursera and is taught using Python. This course is not free but could be a great opportunity to get your feet wet in diving into the machine learning field. Just like any other course, there are pros and cons to it so maybe this will help you decide whether or not it is right for you.

   First, I would like to mention that this course is very organized and goes into the three broad topics of machine learning: supervised learning, unsupervised learning, and neural networks; which is really nice because you get a little bit of each. Each week there is a quiz and a programming assignment to determine if you have sufficient knowledge on the topic to advance. One of the big cons of this program is that it uses GraphLab, a Python module that if you are using it for commercial purpose, is not free. However, if you are just trying to learn how data scientists organize and use data to predict and classify things, it is a great start but remember that you will not be able to use GraphLab outside of this course without paying for it. Honestly, I am seasoned enough as a data scientist that this course was kind of a review of previous things I have already learned in the courses that I have already taken so I will not be continuing the other parts of this course. However, I would recommend this course if you have sufficient experience programming in Python and have very very little experience doing machine learning tasks. Each week in the course takes about two to three hours to complete and each section of the course has about six weeks of material so it is a longer commitment than most.

   I hope you take the time to look into this course and decide for yourself if it is the right fit for you and good look on your own journey into becoming a data scientist!

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