[Fall 2014] Topics in Artificial Intelligence: Machine Learning with Large-scale Data

General Information

Time: Mondays 12:00 - 3:00 PM Place: CBIM 22
Instructor: Tina Eliassi-Rad Office hours: Mondays 3:00 - 4:00 PM in CBIM 08
Course number: 16:198:598 Credits: 3


This graduate-level course covers machine-learning algorithms, programming environments, and software frameworks that are designed to effectively deal with large-scale (i.e., big) data.

Prerequisites: A previous course on machine learning or data mining. A strong knowledge of algorithms and programming (Java, C, and scripting/dynamic languages).




You will be evaluated based on student presentations (40%) and a substantial semester-long project (60%). The project must include at least one big data set, at least one learning/mining algorithm, and a real-world application. For the project, you will need to prepare a proposal, give a presentation at the end of the semester, and write a final report. More details will be provided in class.

Notes, Policies, and Guidelines

Schedule / Syllabus (Subject to Change)

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