Computing for Data Analysis

This could have been a very meaningful course, however, the key issues here were:

1. Content delivered (i.e. lectures and homework assignments) did not reflect the content tested. That is, the content tested was very different from the content delivered.

If you have lots of time on your hands, this may not be an issue (as you can spend time teaching yourself greater depths of knowledge from other sources).

Having said that, you still wont know what what topics to study outside of the course, because you will not know what topics will ultimately be tested in the exams (i.e. anything can be tested).

For example, in the final last year, the very first question (which you needed to solve in order to do the remaining questions) was not covered in any of the content delivered. In fact, the professor even stated as much when reviewing the solutions to the final exam: "You would have noticed the first question was a topic we've not yet covered..."

Personally, I don't see the point of making a subject "hard" simply by testing material not covered.

Better would have been, to cover all the necessary content, and then have challenging exams around that content.

2. The content writing style was extremely unclear and overly complicated.

Whether this was due to the professor inability to think clearly (a usual sign of which is reflected as messy, disorganised and unnecessarily complicated writing), or by design, is not relevant. This is a course that's designed to teach and educate (and it comes with a cost). We are paying for quality content.

Quality content (of which Georgia Tech prides itself) should be reflected in quality thinking (i.e. simplicity, clarity, and organised thinking). This is evidenced by clear writing styles and is important for Georgia Tech (GT) to get this right, because, GT states this course is designed for people who are working full time.

Messy, unclear and disorganised writing simply takes too long to decipher and is therefore not supportive toward people working full time (or who are time-short in general).

My suggestion: Take this course if you're already a programmer and or have lots of experience in this space (and you need to tick this box off as part of the online master of analytics program), and or, you have a lot of time on your hands.

Otherwise, don't do it. There are far better courses out there that teach this material a far more meaningful ways.

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 other cases, the answers were already filled in for the exam problems. And, during the final, the Vocareum system crashed. That was VERY frustrating. Support during the exams was non-existent. Edx was not helpful because the Vocareum system is a completely separate system. Vocareum didn't really have any support. In the end, I sort of just gave up trying to take the final exam due to the technical issues with Vocareum. (Also, you have 36 hours to complete the exams once you start them.) The discussion forums were not much help either. Most students that take the courses are doing so through Georgia Tech, which has its own platforms for student collaboration. The instructor and the TAs don't monitor the discussion forums (that I could see.) And, when I tried to e-mail the instructor, I got no response. Not surprising when you consider the large number of people that were taking the course.

I am taking the course for free (audit), I am not sure if the exam experience is better for people who paid for the course, or GaTech students. I guess I will find out in the Spring when I take the course for credit.

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 problem has been corrected within a day or two.
The video lectures do not match the quality of the notebooks. The teacher seems knowledgeable but only provides a high level overview, avoiding any mathematical details, and there is only about 30 minutes of video materials per week, which is not enough for a beginner in numerical methods and Python. On the other hand for a college student this course is probably the best refresher of the first year college material and a great introduction to Python, equally good, if not better than MIT's "Introduction to Computer Science and Programming Using Python" and "Introduction to Computational Thinking and Data Science". The difficulty level in this course reaches completing an implementation of Conway's Game of Life, operations on sparse matrices, and image compression using PCA.

The problem with the Audit mode in this course is that there is no interaction with the staff on the forum,
but this is stated in the syllabus. Fortunately the quality of the course is high enough that an interaction
is not really needed, contrary to other, much lower quality courses available from GTx on edx.