Bachelor of Science in Applied Computing with Concentration in Data Analytics

University of Saskatchewan

Canada,Saskatchewan

 0 Shortlist

48 Months

Duration

CAD 31,983/year

Tuition Fee

CAD 120

Application Fee

May 2025

Apply Date

Canada, Saskatchewan

Type: University

Location Type: Urban

Founded: 1907

Total Students: 25,900 +

Int. Students: 3,100 +

Campus Detail

Main Campus Address

Saskatoon, SK, Canada

Bachelor of Science in Applied Computing with Concentration in Data Analytics

Program Overview

Computing is permeating modern life and data is the new resource that industries around the world are chasing. However, data analytics or applied computing cannot be taught in isolation. When applied to a particular problem or domain, knowledge of computing and the domain itself are required to effectively achieve insight. A degree in applied computing will give graduates knowledge in both computing and domains of application.

Data Analytics Concentration
Data analytics has become a major growth area of IT, penetrating many more traditional industries with the promise of increased efficiency. Whether it is modeling customers for business, crops for agriculture, or voting intensions for politicians, data analytics has changed the way that we measure, model and understand the world we live in. Data analytics requires significant cross training in computer science, mathematics and statistics, as well as knowledge in the domain of application.

This program trains students in the mathematical theory and computational tools and techniques of data analysis. Data is now a core business commodity used to analyze everything from stock market performance to the voting intentions of particular groups, to the conservation status of protected species. Underlying these complex analyses are mathematical and computational tools that allow the manipulation of large amounts of data to extract meaning.

The data analytics concentration combines courses in computer science and mathematics and statistics to provide knowledge and skills in several critical areas: fundamentals of computer programming and practice, the fundamentals of data analytics, mathematical fundamentals for modelling, statistical measurement and reasoning, and machine learning.