Program Overview
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.
International Students: See Admission Policies for details.
Laptop Requirements
MINIMUM RECOMMENDED HARDWARE
- 64-bit current generation Intel i5 or i7 (preferred) or AMD equivalent.
- 8 GB (16 GB of RAM Preferred)
- 1 TB hard drive
- Ethernet Network Card
- Wireless Network Card
- One USB 3.0 port (two preferred)
- 3 Yr. comprehensive parts and labour (Recommended)
SOFTWARE REQUIREMENTS
- Windows 10 Professional Edition or newer
Courses
The curriculum below is for incoming students:
For pre/co-requisites, please refer to the course outlines.
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 |
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.