The Answer? 1,017

Over the course of almost 3 years, I took 10 courses at Georgia Tech, specializing in Machine Learning.

Overall, I would say the value of the course was perfectly correlated with the amount of hours spent on the course (go figure).

Below is a chart showing the semester I took the class, the colloquial short name for the course via reddit r/omscs, and the hours spent on that course.

Summary

What this class is

This class is a good introduction to network security topics. It also covers a wide range of adjacent academic papers and their theoretical implementations. This class is mainly project based with quizzes and the final exam a small weight of it. Some of the concepts require solid computer network fundamentals and some exposure to security concepts. This class required mild programming in python and JavaScript. The class utilizes Gradescope for all project except project 5, so you know how you are doing as you complete them.

Summary

What this class is

Overall, this class follows what a lot of the other reviews have stated. The lectures and material are not too complicated so that a data science wizard can breeze through or a non-CS major can learn it with a little bit of effort. The lectures, readings, and assignments build upon one another and this continuity was refreshing compared to other classes. The exams are easy if you study the lectures and readings for 5 hours (assuming you reviewed them throughout the class originally). Every assignment has a video or example that you can follow along to get an idea of how to do it. Assignments are not open ended, which is great for an intro to ML concepts. The python programming required is all numpy, and pandas-based. Review numpy and pandas prior to the course. The project descriptions are not as fleshed out as they should be, so fulfilling the requirements can be time consuming and annoying. However, with a little bit of effort on reading the project descriptions and watching the videos anyone can get an A.