Nipissing University
Data Science
| School: | Nipissing University |
| Faculty: | Faculty of Arts and Science |
| Degree: | Bachelor; Honours |
| Field of Study: | Analysis and Functional Analysis
Applied Mathematics
Applied Mathematics, Other
Computational Mathematics
Computer and Information Sciences, General
Computer Science
Data Science, General
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| Description: | The Bachelor of Science (BSc) in Data Science program leads to an undergraduate degree which provides graduates with the necessary mathematical and computational background to be a data scientist. It will introduce you to the applications of data science in your area of interest. Obtaining the degree will involve a combination of courses and experiential learning components in the form of a research paper, practicums and internships.
Whether you are interested in precision medicine, dealing with data sets on environment or business analytics, or understanding complex systems, you will learn how to use the tools and problem-solving skills of computer science and mathematics to work with data. |
| URL: | Data Science at Nipissing University |
| Course Based: | Yes |
| Length: | 4 Year(s) |
| Cost per year:* |
Tuition is based on 30 credits per year (5 courses in each of the fall and winter semesters). The cost of tuition does not include ancillary fees. |
| Scholarships: | 5 |
| Careers: | 7 |
| Grade for Entrance Previous Year (%)* | 70 |
| Prerequisites:* | These courses are intended as guidelines. Speak to your guidance counsellor to see what courses are offered at your school. - Grade12 English
- Grade12 Advanced Functions
- Grade12 Calculus and Vectors
- Grade12 Biology or Grade12 Chemistry or Grade12 Physics
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* The entrance grade may change from year to year. Please contact the school for further information.
* We make every attempt to provide accurate information on prerequisites, programs, and tuition. However, this information is subject to change without notice and we highly recommend that you contact the school to confirm important information before applying.
