CS 109B: Advanced Topics in Data Science
Pavlos Protopapas and Mark Glickman
- Pavlos: Mondays 3-4pm at MD G108
- Mark: By appointment
Head TF: Eleni Kaxiras firstname.lastname@example.org
Head TF for DCE: Sol Girouard email@example.com
Lectures: Mon and Wed 1:30‐2:45pm in Maxwell-Dworkin G-115
Labs: Thur 4:30-6:00pm in Pierce 301
Advanced Sections: Wed. 3:00pm-4:15pm, location TBD (starting 2/13)
Prerequisites: CS 109a, AC 209a, Stat 121a, CSCI E-109a or equivalent.
Data Science 2 is the second half of a one-year introduction to data science. Building upon the material in Data Science 1, the course introduces advanced methods for data wrangling, data visualization, and deep neural networks, statistical modeling, and prediction. Topics include big data and database management, multiple deep learning subjects such as CNNs, RNNs, autoencoders, and generative models as well as basic Bayesian methods, nonlinear statistical models and unsupervised learning.
IGNITE TALKS SCHEDULE is here
Module 1: A Real-Bogus Classifier (1:30 - 2:45pm) - Mon. 4/22, and Wed. 4/24 in NW B-103?
Module 2 : Microbiome (1:30 - 2:45pm) - Mon. 4/22, Wed. 4/24, and Mon. 4/29 in MD-115
Due Dates for the Final Project/Modules deliverables
4/17 - Milestone #1
4/27 - Milestone #2
5/12 - Peer Evaluation
5/12 - Milestone #3 (Final)
5/13 and 5/14 - Ignite Talks Presentation (each group will choose ONE date of the two)
Instructions for using JupyterHub: Instructions for Using SEAS JupyterHub
Video-recorded Lectures from CS109A Fall '18
Advanced Sections take place in NW B-103
Pierce Hall is at 29 Oxford St in Cambridge.
Maxwell Dworkin (MD) is at 33 Oxford St, Cambridge.
Northwest Building (NW) is at 52 Oxford St, Cambridge.
Office Hours : Weekly Schedule
For enrollment issues including cross-registration: contact the FAS Registrar's Office either in person at the Smith Campus Center (1350 Massachusetts Avenue, Suite 450) or by sending an email to firstname.lastname@example.org