DS 501: Introduction to Data Science

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.