Microsoft DAT208x: Introduction to Python for Data Science, a review

In my quest to complete the Microsoft Professional Program for Data Science, I took their course Introduction to Python for Data Science earlier this month to disappointing results.

It could be that I had very different expectations, or that I already have too much background in Python for another introductory course, but I wasn’t impressed and I’m loath to pay for the verified certificate.

This felt more like an overview than a proper introduction. If this was a university, this would have been the first day when the instructor gives out the syllabus and walks through the course expectations.

Would I discourage you from taking the course? Yes actually.

(To follow my progress on the program, check out the Microsoft Professional Program tag)


The Structure

DAT208x claims to “cover Python basics and prepare you to undertake data analysis using Python”. Similar to the Microsoft courses that come before it, it is a self-paced course comprised of video lectures and lab exercises.

The modules are as follows:

  1. Python Basics
  2. Lists
  3. Functions and Packages
  4. Numpy
  5. Plotting with Matplotlib
  6. Control Flow and Pandas

This course is brought to you by a partnership between Microsoft and Data Camp, the latter an online Data Science school similar to DataQuest. In an old post I mentioned my apprehension with Data Camp as I’ve heard they favor R over Python, but I decided to give them the benefit of the doubt and give their Python course a try.

Its due to this partnership that most of the lab activities are outside of edX. i.e., we’re redirected to DataCamp’s interface for the lab exercises.

These exercises are the meat of the course. If you’ve tried DataQuest before then the DataCamp interface should be familiar:

Instructions are to the left, interactive Python shell to the right. After submitting your answer DataCamp verifies if your code is correct.

Unlike other Microsoft courses I’ve tried, this one has a final exam. In this exam you are given 4 hours to answer 50 questions: a mixture of knowledge checks, pseudo coding, and actual coding.

Considering the quizzes, exercises, and final exam, you need to score at least 70% to pass the course. Pretty easy considering 40% is just course surveys.


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Microsoft DAT101x Data Science Orientation Review

At $25 (beta price), this orientation course is overpriced for what it offers.

Update: To follow my progress in this program, check the Microsoft Professional Program tag.


I’ve mentioned in my Getting Started with Data Science tips that I’m currently taking the Microsoft Professional Program for Data Science.

The program is still in beta, so:

1. Microsoft needs the feedback, and

2. Potential students would want to know if the program will be worth their time, money, and effort.

The program is pretty extensive, so I thought it best to break my reviews by course as I take them. This review is on the orientation course, DAT101x Data Science Orientation.

For context, I took the course around late September 2016, and got my certificate early October.


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Getting Started with Data Science, for the complete beginner

If you found this page, it means two things:

1. You are interested in data science, but aren’t sure where or how to begin.
2. My SEO skills are improving.

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If you found this page, it means two things:

  1. You are interested in data science, but aren’t sure where or how to begin.
  2. My SEO skills are improving.

I might be able to help with #1. I can tell you what I’ve done so far and of those, what worked. Maybe you’ll pick up a tip or two, and I will be able to do the post title justice.

#2… Let’s leave it at that.

You might be wondering what credentials I have to say I can help you out. I don’t have any. I’m a complete data science newb. But, why would I need credentials for wanting to help?

If you know less than I do, I can teach you.

If you know more than I do, you can teach me.

If you and I are on the same level, we can help each other learn.

That’s the idea behind this post.

I won’t go into defining what data science is (and its related terms, such as big data and data analytics). I will assume that your finding yourself here means you’ve already googled all that. What I will do is talk you through what I’ve tried so far that has worked for me, and maybe those would help you too.

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