Advanced Topics in Data Science

Harvard Extension School

CSCI E-109B

Section 1

CRN 26501

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Building upon the material in CSCI E-109a, the course introduces advanced methods for statistical modeling, representation, and prediction. Topics include multiple deep learning architectures such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), transformers, language models, autoencoders, and generative models, as well as basic Bayesian methods and unsupervised learning. Students are strongly encouraged to enroll in both the fall and spring course within the same academic year. Students who have previously completed CSCI E-107 or CSCI E-109 may not take CSCI E-109a or CSCI E-109b for degree or certificate credit.

Credits: 4

Term

Spring Term 2026

Part of Term

Full Term

Format

Online

Credit Status

Graduate

Section Status

Open

Instructor Info

Pavlos Protopapas, PhD

Scientific Program Director and Lecturer, Institute for Applied Computational Science, Harvard University

Kevin A. Rader, PhD

Senior Preceptor in Statistics, Harvard University

Meeting Info

1/26 to 5/16

Participation Option: Online Asynchronous

Deadlines

Last day to register:

Additional Time Commitments

Required sections to be arranged.

Prerequisites

A grade of B-minus or higher in CSCI E-109a. Students who have not completed CSCI E-109a should contact the instructors before registering.

Notes

The recorded lectures are from the Harvard John A. Paulson School of Engineering and Applied Sciences companion course Computer Science 1090b. Registered students can ordinarily live stream the lectures Mondays and Wednesdays, 9:45-11 am starting January 26 or they can watch them on demand. The recorded sessions are typically available within a few hours of the end of class and no later than the following business day. Class sessions for this course may include students enrolled in the FAS companion course. Accordingly, when you participate in live class sessions, you will do so alongside both Division of Continuing Education (DCE) and FAS students. If you participate in a way that causes you to appear in recordings of the class, those recordings may be shown to DCE students enrolled in this course or FAS students enrolled in the companion course, according to the policies of the two schools on accessing recordings of class sessions.

Tuition

All Sections of this Course

CRN	Section #	Participation Option(s)	Instructor	Section Status	Meets	Term Dates
26501	1	Online Asynchronous	Team Taught	Open		Jan 26 to May 16