Welcome to BST261: Data Science II

Deep learning is a subfield of machine learning that builds predictive models using large artificial neural networks. Deep learning has revolutionized the fields of computer vision, automatic speech recognition, natural language processing, and numerous areas of computational biology. In this class, we will introduce the basic concepts of deep neural networks and cloud computing, discuss basic neural networks, convolutional neural networks and recurrent neural networks structures, and examine biomedical applications. Students are expected to be familiar with linear algebra, python and machine learning.

All course material will be posted here. See below for assignment deadlines.

NOTE: all lectures, labs and office hours will be held via Zoom. The links to each meeting can be found on the course Canvas site.

Course Instructor

Heather Mattie
Lecturer on Biostatistics Harvard T.H. Chan School of Public Health
Building 1 Room 421A, 655 Huntington Ave, Boston
[email protected]
Office hour: Mondays 8-9pm or by appointment

Course Teaching Assistants

Beau Coker PhD Candidate, Biostatistics
[email protected]
Office hour: 1-2pm EST

Gopal Kotecha PhD Candidate, Biostatistics
[email protected]
Office hour: Wednesdays 4:30-5:30pm EST

Lab: TBD

Lab material and problem sets can be found in this Google Drive folder.

Problem Set 1: Due April 9 by 11:59pm ET

Problem Set 2: Due May 7 by 11:59pm ET

Group Project Proposal: Due Friday, May 14th by 11:59pm ET

Paper presentations will take place throughout the course starting week 2 and must be recorded and posted to a discussion board on the course Canvas site.