Last week, I completed my first semester as a Data Science Master’s student. Over the 14 weeks, I learned a bunch about a wide variety of topics, especially in DS 501.
|Pre-Spring Break||Post-Spring Break|
|1/20: Introduction||3/16: Machine Learning Part 2|
|1/27: Data Gathering||3/23: Visualization|
|2/3: Data Storage||3/30: Large-Scale Data Analysis|
|2/10: Business Intelligence||4/6: Graph Data|
|2/17: Basic Statistics, Probability, and Linear Algebra||4/13: Graph Data and High Dimensional Data|
|2/24: Machine Learning Part 1||4/20: Deep Learning|
|2/2: Midterm Exam||4/27: Final Exam|
My classes tackled everything—from collecting and storing tweets in MongoDB, using the Twitter streaming API, to performing textual analysis of movie reviews using Scikit-Learn.
Even though I could have learned all these things on the Internet, the interactive, class-based structure made it more worthwhile.
The next semester starts May 16th!
All my code, including problem sets and lecture notes, is on GitHub.