My Experience with Data Science Bootcamps, Part 2
This blog post is part of a series to give people interested in Data Science bootcamps in Seattle an overview of my experience. This post will cover my experience with Galvanize's Data Science Immersive program. If you want more information on my background, previous work and my experience with General Assembly Seattle, check out this post.
Galvanize's Data Science Immersive Program
Below is the schedule as is advertised on the Galvanize Data Science website:
Week 1 - Exploratory Data Analysis and Software Engineering Best Practices
Week 2 - Statistical Inference, Bayesian Methods, A/B Testing, Multi-Armed Bandit
Week 3 - Regression, Regularization, Gradient Descent
Week 4 - Supervised Machine Learning: Classification, Validation, Ensemble Methods
Week 5 - Clustering, Topic Modeling (NMF, LDA), NLP
Week 6 - Network Analysis, Matrix Factorization, and Time Series
Week 7 - Hadoop, Hive, and MapReduce
Week 8 - Data Visualization with D3.js, Data Products, and Fraud Detection Case Study
Weeks 9-10 - Capstone Projects
Week 12 - Onsite Interviews
Most days started at 8am with a lecture or sometimes a morning quiz. Following the lecture, we would work on the morning assignment, which was typically an individual assignment. Its rare that these morning assignments were ever finished to completion, as most had additional "bonus" tasks. There would then be an hour lunch break, where some students might continue to work on previous assignments or we'd run out into Pioneer Square to get lunch. After lunch was the afternoon lecture, which was often shorter and less technical than the morning lecture. Following the lecture, we would split up into our pairs for the day (we would get a new pair each day) and complete the afternoon assignment. One of the biggest challenges during this time was working as a pair using GitHub for version control between pairs. If I can give a piece of advice for people preparing for this program, become comfortable with git and branch management if you are not already. Once you were done (whatever that meant to you that day) with the pair assignment, you were free to go home.
The Support Team
Throughout the course, we had three main instructors - all of whom had PhDs and lots of industry experience. In addition, there are two Data Scientists in Residence (DSRs) who are students from the previous cohort who stay on to TA the next cohort.
I frequently recommend Galvanize to people who ask. The quality of instruction that I received there was phenomenal and they make sure to screen potential students heavily to ensure that you can handle the difficulty of the curriculum. In addition, one of the most valuable things I got from my time there was networking and career coaching, which ensures that you are set up for success.