CST383 - Module 8

What did I learn in the eighth week of CST383?

This is the final week of the course. Basically, we simply went over everything that was gone over throughout the course such as data acquisition, data cleaning, preprocessing, data exploration, visualization, and machine learning. It was a very comprehensive study guide we needed to fully understand, but thanks to the professor providing us a cheat sheet (front & back) and ample study time, it wasn't too difficult to get behind, especially when referencing specific aspects from prior quizzes to fully understand any or all expectations before the final exam.

This was honestly the most informative and extensive course I have taken throughout the entire program. Although, I do wish there were more examples over math and visualization. Nevertheless, machine learning took the most time to review, since comparing KNN, linear regression, and logistic regression required constant consideration with what was displayed for bias-variance tradeoff.

In the end, other than a few hiccups with course materials and clarification on course requirements, this has honestly been the most informative course I have ever taken. 

I hope that everyone else has the same sentiment.