1. Nipissing University
  2. Program
  3. Bachelors
  4. Bachelor of Science (BSc) in Data Science

Bachelor of Science (BSc) in Data Science

4 Years On Campus Bachelors Program

Nipissing University

Program Overview

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.

Program Key Stats

Rolling


Eligibility Criteria

2.7
30
80

1180
6.5
86

Additional Information & Requirements

Students must complete 120 credits, with a minimum overall average of 60%, and satisfy one of the following:Honours Specialization:Must complete 60 credits in the honours specialization, including at least six credits at the 4000 level (according to details provided in the Program Requirements section);Must achieve a minimum honours specialization average of 70% (based on the best 60 credits which meet all of the honours specialization requirements);Not exceed a maximum of 48 credits at the 1000 level;Not exceed a maximum of 84 credits in one discipline (may not have the same four-letter code);Must complete six credits from each the following areas:Humanities (Group I)Social Sciences (Group II) and/or Professional Studies (Group IV)Must complete a minimum of 12 credits in a science discipline other than that of their area of study;Must successfully complete ACAD 1601 within the first 60 Nipissing credits. ACAD 1601 will count towards three credits of the Humanities (Group I) requirement.

Career Options

  • Data Scientist
  • Machine Learning Engineer
  • Machine Learning Scientist
  • Applications Architect
  • Enterprise Architect
  • Data Architect
  • Infrastructure Architect
  • Data Engineer

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