Data Science
Email Address: Carson.Leung@umanitoba.ca
Website: umanitoba.ca/explore/programs-of-study/data-science-bsc
Data Science
The Faculty of Science offers an interdisciplinary 4-year Major program in Data Science. Data Science is an emerging field of study that combines computer science, mathematics and statistics to collect, analyze, visualize and interpret data.
Programs
| Degree/Diploma | Years to Completion | Total Credit Hours | Has Co-op Option |
|---|---|---|---|
| Degree/Diploma Data Science, B.Sc. Major | Years to Completion 4 | Total Credit Hours 120 | Has Co-op Option Yes |
Courses
Data Science
DATA 2010 Tools and Techniques for Data Science 3 cr
(Lab required) An introduction to the field of data science with an emphasis on the fundamental tools and techniques that underlie the field of data science.
PR/CR: A minimum grade of C is required unless otherwise indicated.
Prerequisites: [one of MATH 1240, MATH 1241, or the former COMP 2130] and [one of MATH 1220, MATH 1210 (B), MATH 1211 (B), MATH 1300, or MATH 1301] and [one of MATH 1232, MATH 1700, MATH 1701, or MATH 1710]. Pre-or corequisites: COMP 2140 and STAT 2150.
Prerequisites: [one of MATH 1240, MATH 1241, or the former COMP 2130] and [one of MATH 1220, MATH 1210 (B), MATH 1211 (B), MATH 1300, or MATH 1301] and [one of MATH 1232, MATH 1700, MATH 1701, or MATH 1710]. Pre-or corequisites: COMP 2140 and STAT 2150.
Attributes: Science
DATA 3010 Data Science with Real World Data Sets 3 cr
(Lab required) This course will expose students to real-world data sets in the study of data science. May not be held with COMP 3360.
PR/CR: A minimum grade of C is required unless otherwise indicated.
Prerequisite: DATA 2010.
Prerequisite: DATA 2010.
Mutually Exclusive: COMP 3360
Attributes: Science
DATA 4010 Data Science Capstone Project 6 cr
A project course where students apply the knowledge and skills acquired in earlier coursework to a substantial data science problem. It will enable the development of soft skills, and explicit consideration of important topics including Ethics, Communication, Data Privacy, Data Presentation and Insight Delivery, all of which are key elements for a training in Data Science, beyond the technical content. This course is restricted to Faculty of Science students in the Data Science Major or Major Co-op. Students are expected to take this course in their final year.
PR/CR: A minimum grade of C is required unless otherwise indicated.
Prerequisites: DATA 3010 and permission of the instructor.
Prerequisites: DATA 3010 and permission of the instructor.
Attributes: Science