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Computing for Data Analysis

Georgia Institute of Technology via edX

students interested

Please note that the verified certificate option is not currently open for this course. Please enroll in the audit track and you will be emailed when the verified certificate option is open for enrollment.

The modern data analysis pipeline involves collection, preprocessing, storage, analysis, and interactive visualization of data.

The goal of this course, part of the Analytics: Essential Tools and Methods MicroMasters program, is for you to learn how to build these components and connect them using modern tools and techniques.

In the course, you’ll see how computing and mathematics come together. For instance, “under the hood” of modern data analysis lies numerical linear algebra, numerical optimization, and elementary data processing algorithms and data structures. Together, they form the foundations of numerical and data-intensive computing.

The hands-on component of this course will develop your proficiency with modern analytical tools. You will learn how to mash up Python, R, and SQL through Jupyter notebooks, among other tools. Furthermore, you will apply these tools to a variety of real-world datasets, thereby strengthening your ability to translate principles into practice.

Taught by

Richard W. Vuduc


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Reviews for edX's Computing for Data Analysis
2.5 Based on 2 reviews

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2.0 2 months ago
Anonymous is taking this course right now.
Overall, I think the content of the course is very good. However, the execution is beyond terrible. There is really no reason this should be an "EdX" course, as they do not use any EdX technology for the course. Not the discussion boards, not the assignments. I guess you can count the videos. The videos need work. There may be 10-15 total minutes of videos for each topic that do not even teach anything, they basically go over what the assignments will be. After taking some other classes on Edx that I felt were really really great, I am pretty disappointed with this class. If I wanted to teach myself everything about the topic, I would not have paid for an EdX course.
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3.0 5 months ago
by Spalthoff Daniel dropped this course, spending 15 hours a week on it and found the course difficulty to be hard.
I dropped out of this course after four weeks, for personal reasons (travel, work). The course was very demanding, but interesting. However, course support was not sufficient. Recitations with tutors were offered, but suitable only for American time zones. Although a second recitation time slot was announced, this was not accessible for edX students. As I found the course very interesting, I will probably give it another try in the future; but I hope the support for edX students will be better.
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