Artificial Intelligence & Business Analytics

Program Overview

Artificial Intelligence & Business Analytics

The Artificial Intelligence & Business Analytics Diploma Program at Alpha Community Outreach is a 60-week program that offers the opportunity to become a skilled professional in the field of artificial intelligence.

This diploma is designed to equip students with both foundational and specialized knowledge in Artificial Intelligence (AI) and its application in business environments. The program combines technical AI skills with business analytics, preparing graduates to support data-driven decision-making and business optimization across a variety of industries.

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Artificial Intelligence & Business Analytics

Employment Outlook

Salary & Outlook

Graduates enter a high-demand sector with competitive wages across Canada. Health and social community services represent one of the fastest-growing job segments.

47.69

Average Wage/HR**

100

High Wage/HR**

Source: workingincanada.gc.ca
‍NOC Code: NOC Code: 14200, 12200 – Wage data based on NOC code 12200 and rounded down to the nearest dollar. Average wage doesn’t reflect the starting salary but represents the middle value between lowest to highest wages. Local (or regional) income may vary. Last updated: December 2024.

Curriculum Details

Course Information

1 Course Details

Alpha Community Outreach requires that students enrolled in the Artificial Intelligence & Healthcare Applications. Program complete all the courses listed below. To receive a diploma a student must receive a minimum mark of 60 in all compulsory courses.

PROGRAM STRUCTURE

Semester 1 – Core Courses (Weeks 1–25)
1. Foundational AI & Ethical Practice
2. Python for Data Science
3. Data Analytics and Visualization
4. Core Machine Learning and Statistical Modeling

Semester 2 – Specialization Courses (Weeks 26–55)
Students focus on business analytics applications.
1. Predictive Analytics for Business
2. AI in Finance & Marketing
3. Operations & Supply Chain Analytics with AI
4. Advanced Machine Learning Applications
5. Business Decision-Making with AI
Semester 3 – Capstone Project (Weeks 56–60)

Students complete a practical AI project in business analytics, applying skills from core and
specialization courses to solve a real-world problem.

2 Course Listings

Foundational AI & Ethical Practice

This course introduces core artificial intelligence concepts and ethical considerations in AI deployment. Students examine responsible data use, bias mitigation, and regulatory awareness in AI systems.

Python for Data Science

This course develops programming proficiency in Python for data analysis applications. Students learn to manipulate datasets, automate tasks, and build analytical scripts for business and research use.

Data Analytics and Visualization

This course focuses on interpreting and presenting data to support informed decision-making. Students learn analytical techniques and visualization tools to communicate insights clearly and effectively.

Core Machine Learning and Statistical Modeling

This course introduces supervised and unsupervised learning models alongside essential statistical methods. Students build and evaluate predictive models to solve real-world analytical problems.

3 Admission Requirements

Students must meet one (1) of the following admission requirements:

High school graduation or
GED or equivalent or
Mature student – Detailed resume outlining experience and qualifications must be submitted.

Admission Equivalent, Mature student, technical and language requirements:

Equivalent: Foreign credentials must be translated in English and assessed for Grade 12 equivalency by a recognized organization, or
Mature student with a score of 11 or more on the Wonderlic SLE (or other MCU approved test) Note: CAT and CAST no longer approved. AND
NACC Technical Literacy Exam (passing score of 18), or
IELTS – Int’l English Language Testing Services – Minimum score of 6.0 with no subject test score lower than 5.5; or
TOEFL – Test of English as a Foreign Language Internet based test (IBT) – Overall 80 with the minimum in each component: Reading 20; Listening 20; Speaking 20; Writing 20.

Artificial Intelligence & Business Analytics

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