Class Restriction And Registration Summary


CSE 64648 - Section 01: Data Science (Online) (CRN 3552)

Course Description:
Data science can be viewed as the art and craft of extracting knowledge from large bodies of structured and unstructured data using methods from many disciplines, including (but not limited to) machine learning, databases, probability and statistics, information theory, and data visualization. This course will focus on the process of data science -- from data acquisition to analytics methods to deployment, and will walk the students through both the technical and use-case aspects in the process. It will place a larger emphasis on the machine learning component, with relevant inclusions and references from other disciplines. The course will give students an opportunity to implement and experiment with some of the concepts as part of a class project, in addition to the hands-on assignments using the Python programming language. Additionally, the course touches upon some of the advances in related topics such as big data and discuss the role of data mining in contemporary society. The course has been designed and developed by Nitesh Chawla, the Frank Freimann Professor of Computer Science and Engineering and Director of iCeNSA at the University of Notre Dame.

Note: this course is delivered fully online. The course design combines required live weekly meetings online with self-scheduled lectures, problems, assignments, and interactive learning materials. To participate, students will need to have a computer with webcam, reliable internet connection, and a quiet place to participate in live sessions. Students who will be on the Main campus are not eligible to enroll in this course.

No financial aid is available for this course.

Students enrolling in this course should have taken one or more courses or implemented one or more projects involving Python programming and one or more courses in probability or statistics.

Associated Term: Summer Session 2018
Campus: Online Digital Learning
Credits: 3
Grade Mode: Standard Letter
Course may not be repeated

Must be enrolled in one of the following Levels:
Employee Non-Degree (EM) ,  Graduate Architecture (GA) ,  Graduate Non-Degree (GD) ,  Graduate (GR)

Course Attributes:
OLF-Fully Online (100 percent) ,  ZODO - Online Digital Learning

Registration Availability (Overflow: Off )
  Maximum Actual Remaining
TOTAL 5 0 5

Crosslist Information
Class Information Maximum Actual Remaining
CSE  44648 01, CRN 3487  (Primary) 36 14 22
CDT  44640 01, CRN 3500   4 2 2
CSE  64648 01, CRN 3552   5 0 5
Total 45 16 29