Data Mining, Discovery, and Exploration
Harvard Extension School
CSCI E-108
Section 1
CRN 26492
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.
Registration Closes: January 23, 2025
Credits: 4
View Tuition Information Term
Spring Term 2025
Part of Term
Full Term
Format
Flexible Attendance Web Conference
Credit Status
Graduate, Noncredit, Undergraduate
Section Status
Open