Data Analytics for Business | St. Clair College
Program Code: B018
Status: Open
Apply Online:
Program Code: M018 & M019
Status: Open
Apply Online:
Two Year - Ontario College Graduate Certificate
Starts: September

Emergency Alternate Delivery Plan:
Winter 2024 Emergency Alternate Delivery

Contact:
John Ulakovich
519-972-2727 ext. 5858

Program Overview

The Data Analytics for Business 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

Diploma or degree in a relevant field from a recognized college or university or demonstrated competence through related work.

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:

Semester 1
Code Title Credits
DAB100
Introduction To Data Analytics
3
DAB501
Basic Statistics And Exploratory Data Analysis
5
DAB106
Introduction to Artificial Intelligence
3
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
5
DAB304
Healthcare Analytics
5

Past Cohorts:

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
DAB103 Analytic Tools And Decision Making 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
DAB300 Machine Learning II 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
Semester 1
Code Title Credits
DAB100 Introduction To Data Analytics 3
DAB501 Basic Statistics And Exploratory Data Analysis 5
DAB101 Introduction To Artificial Intelligence 2
DAB102 Information Management 3
DAB103 Analytic Tools And Decision Making 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
DAB300 Machine Learning II 5
DAB301 Project Management Analytics 4
DAB302 Ethics For Analytics 2
DAB303 Marketing Analytics 5
DAB304 Healthcare Analytics 5
Semester 4
Code Title Credits
DAB400 Supply Chain Analytics 5
DAB401 Financial Analytics 5
DAB402 Capstone Project 10

Your Investment

The standard tuition and compulsory fees for the current academic year:

2023-2024 Tuition Fees  

For programs with Experiential Learning (Work Placement/Internship): Costs for accommodation, if needed, travel and related expenses is 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 through 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

Data Analytics for Business (Ontario College Graduate Certificate) (70717)

The graduate has reliably demonstrated the ability to:

  1. Analyze, organize, and manipulate data to support problem-solving, business decision-making, and opportunity identification.
  2. Develop statistical and predictive models that use business-relevant data to identify patterns and provide insights to business stakeholders.
  3. Assess and apply business intelligence and data science tools appropriate to the business decisions, business problems, data movement, and system workloads.
  4. Prepare and communicate complex materials verbally, in writing, and digitally for a variety of audiences, purposes, and levels of detail.
  5. Prepare, analyze and interpret data as it relates to various aspects of a business organization’s needs.
  6. Conduct data analysis and research in a respectful and ethical manner that protects privacy and maintains dignity to all involved.
  7. Deliver data-oriented projects using data science, business analysis, and project management principles, tools, and techniques to ensure clients' business needs are achieved.

Additional Information