Data Mining, Discovery, and Exploration

Harvard Extension School

CSCI E-108

Section 1

CRN 26492

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Extracting useful insights and relationships from massive complex data sets is the domain of data mining. Data mining has wide ranging applications in science and technology, including web search, interactions in social networks, recommender systems, processing signals in large internet-of-things (IoT) sensor networks, image search, genetic analysis, and discovery of interactions between drugs. This course surveys a range of unsupervised learning algorithms for data mining. The emphasis is on graph algorithms and scaling for massive datasets. The course comprises readings and lectures on theory along with hands-on exercises and projects where students apply the theory through Python coding. For the hands-on component of the course a variety of libraries in the Python language, including possibly Scikit-Learn, NetworkX, Neo4J, and Surprise are used. Students may not take both CSCI E-96 and CSCI E-108 for degree or certificate credit.

Instructor Info

Stephen Elston, PhD

Principal Consultant, Quantia Analytics LLC


Meeting Info

W 6:00pm - 8:00pm (1/27 - 5/17)

Participation Option: Online Asynchronous or Online Synchronous

In online asynchronous courses, you are not required to attend class at a particular time. Instead you can complete the course work on your own schedule each week.

Deadlines

Last day to register: January 23, 2025

Additional Time Commitments

Optional sections Tuesdays, 6-8 pm.

Prerequisites

Students enrolling in this course are expected to have some background in Python programming equivalent to CSCI E-7 or CSCI E-50 and statistical modeling equivalent to CSCI E-63c, CSCI E-101, CSCI E-106, or STAT E-109. Knowledge of basic linear algebra, equivalent to MATH E-21a, is essential.

Notes

This course meets via web conference. Students may attend at the scheduled meeting time or watch recorded sessions asynchronously. Recorded sessions are typically available within a few hours of the end of class and no later than the following business day.

Syllabus

All Sections of this Course

CRN Section # Participation Option(s) Instructor Section Status Meets Term Dates
35576 1 Online Asynchronous, Online Synchronous Stephen Elston Open MW 6:30pm - 9:30pm
Jun 24 to Aug 9
26492 1 Online Asynchronous, Online Synchronous Stephen Elston Open W 6:00pm - 8:00pm
Jan 27 to May 17