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Computing for Data Analysis

Georgia Institute of Technology via edX

students interested
  • Provider edX
  • Subject Data Analysis
  • $ Cost Free Online Course
  • Session Upcoming
  • Language English
  • Effort 8-10 hours a week
  • Start Date
  • Duration 15 weeks long

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Overview

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
3.3 Based on 4 reviews

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  • 3 star 25%
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  • 1
Spalthoff D
3.0 a year ago
by Spalthoff is taking this course right now, 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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Anonymous
4.0 yesterday
Anonymous completed this course.
For the most part, this was an excellent course. The lectures were well done, and I learned some valuable information, not just about the algorithms, but also about efficiency and accuracy. A good portion of the course involved using Vocareum (hosted jupyter notebooks). That system had several problems. The most frustrating part of the course was the exams. The exam questions were programming problems that had some overlap with the homework exercises. There were several technical issues with the exam platform. In some cases, the required data files were not uploaded to Vocareum. In ot…
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Anonymous
2.0 10 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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Anonymous
4.0 yesterday
Anonymous completed this course.
This is a review of the fall 2018 session. This course offers very high quality jupyter notebooks,

and interesting assignment problems. The notebooks are almost exactly matching https://github.com/cse6040/labs-fa17. Both Verified and Audit students have access to the Vocareum platform, and there is a two week deadline after each of the 15 homework notebooks is released. After the deadline the solution notebooks are provided.

The midterm and final exams had serious problems, since some exercises in the notebooks had the solutions included by mistake, however this probl…
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  • 1

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