The Predictive Data Analytics program prepares students to visualize past, present, and future patterns by linking and presenting information in meaningful ways. The area of data analytics offers deeper insight and meaning of data sets for users by telling the story behind the information. This type of detailed and defined information enables graduates to effectively predict trends, understand the needs of customers, as well as make more informed business decisions.
Students will learn a unique blend of theoretical knowledge and advanced applicable skills. Students will also learn large scale data manipulation, how to collect, curate, encode, and store data sets, which can be analyzed and mined in ways that can be reused and repurposed to solve challenges and predict future patterns for business decision making. Students will gain critical thinking skills that demonstrate the ability to use existing and discoverable data to solve business problems.
Career Opportunities
Graduates may find employment across almost all public or private sectors. Positions within these sectors include data analyst, business analyst, quantitative analyst, digital marketing, project manager, operations analyst, transportation logistics, systems analyst. Those with an entrepreneurial spirit may prefer self-employment opportunities within the field such as data analytics consultants or design of data management solutions.
Admission Requirements
Ontario College Diploma, Ontario College Advanced Diploma, Degree, or equivalent with a concentration in Business, Computer Science, Mathematics or Engineering, or combination of work-related experience and post-secondary experience.
For pre/co-requisites, please refer to the course outlines.
Every effort has been made to align the pre/co-requisite document with the information on the course outline. However, if there are any discrepancies identified, the information on the course outline takes precedence.
Past Cohorts:
Previously Data Analytics for Business - B018/K018/M018/M019
Semester 1
Code
Title
Credits
DAB100
Introduction To Data Analytics
3
DAB501
Basic Statistics And Exploratory Data Analysis
5
DAB106
Introduction To Artificial Intelligence
2
DAB102
Information Management
3
DAB111
Intro To Python Programming
5
Semester 2
Code
Title
Credits
DAB200
Machine Learning I
5
DAB201
Data Visualization And Reporting
4
DAB502
Advanced Statistics For Data Analytics
5
DAB202
IT Service Management
3
DAB203
Business Analytics And Decision Making
4
Semester 3
Code
Title
Credits
DAB311
Introduction To Deep Learning
5
DAB301
Project Management Analytics
4
DAB302
Ethics For Analytics
2
DAB303
Marketing Analytics
5
DAB322
Capstone Project I
4
Semester 4
Code
Title
Credits
DAB400
Supply Chain Analytics
5
DAB401
Financial Analytics
5
DAB422
Capstone Project II
10
DAB304
Healthcare Analytics
10
Your Investment
The standard tuition and compulsory fees for the current academic year:
For programs with Experiential Learning (Work Placement/Internship): Costs for accommodation, if needed, travel and related expenses are at the student's own expense. It is recommended for most programs, that students have access to a laptop or desktop computer while away from home during experiential learning periods.
Textbooks and other materials are in addition to Tuition Fees. Textbook prices may be found on the Bookstore website.
Please be aware that tuition and compulsory fees are subject to adjustment each year. The College reserves the right to change, amend or alter fees as necessary without notice or prejudice.
Program Vocational Learning Outcomes
Predictive Data Analytics (Ontario College Certificate) (MTCU Code 70717)
The graduate has reliably demonstrated the ability to:
Analyze, organize, and manipulate data to support problem solving, decision-making, and opportunity identification
Develop statistical and predictive models that use relevant data to identify patterns and provide insights to stakeholders.
Assess and apply business intelligence and Big Data tools appropriate to decisions, problems, data movement, and system workloads.
Prepare and communicate complex materials verbally, in writing, and digitally for a variety of audiences, purposes, and levels of detail
Analyse and interpret data as it relates to various aspects of an organization’s readiness to change
Conduct data analysis and research in a respectful and ethical manner that protects privacy and maintains dignity to all involved
Deliver data-oriented projects using data science, analytics, and project management principles, tools, and techniques to ensure clients' organizational needs are achieved.