DS3010: DS III: Computational Data Intelligence - D-term 2022

Version: March 9th 2022

Class Information:

Instructor:

Prof. Yanhua Li
Email: yli15 at wpi.edu
Website: http://wpi.edu/~yli15/
Zoom office hour: Fri 10AM-11am by Zoom (see Canvas for the link), Others by appointments

TA: Hang Yin
Office: UH341
Email: hyin@wpi.edu
In-person office hour: Monday 2:00-3:00pm; Friday: 1-2pm, Others by appointments

Course Description:

This course introduces core methods in Data Science. It covers a broad range of methodologies for working with large and/or high-dimensional data sets to making informed decisions based on real-world data. Core topics introduced in this course include data collection through use cycle, data management of large-scale data, machine learning and deep learning. Students will acquire experience with big data problems through hands-on projects using real-world data sets. Recommended background: Data science basics equivalent to DS 1010, and data analysis principles and modeling equivalent to DS 2010, knowledge of basic statistics equivalent to (MA2611 and MA 2612), and the ability to program equivalent to (CS 1004 or CS 1101 or CS 1102) and (CS 2102, CS2103 or CS 2119), as well as understanding of databases equivalent to (CS3431 or MIS3720) are assumed.

Textbook:

The topic is evolving. Thus no one comprehensive text book exists that would contain the material we will study in this course. Instead we will be utilizing a variety of sources, including publications from the primary literature and book chapters. These manuscripts will be provided to the class and/or linked into our schedule.

Coursework and Evaluation:

The grading system for this course is A,B,C,NR (without +/-).
Individual projects: 35% (15% project 1, 20% project 2).
Team project: 25%.
Final Exam: 25%
Quizzes: 15% (2-3 quizzes)
Note:Please see more details of the projects in the projects page.