Artificial Intelligence and Data Analytics

Program Overview

The Post-Graduate Certificate in Artificial Intelligence and Data Analytics (AI&DA) equips internationally-educated graduates with the skills and knowledge to analyze large datasets, develop expertise in Python, understand the ethical implications of AI, and prepare for careers in data analysis and machine learning. The program consists of 32 weeks of intensive study, covering topics such as business mathematics, data engineering, programming for data science, machine learning, and artificial intelligence for management. Graduates are prepared for entry-level positions in data analysis, data science, and machine learning.

Program Outline

Degree Overview:

Overview:

The Post-Graduate Certificate in Artificial Intelligence and Data Analytics (AI&DA) prepares internationally-educated graduates with degrees in Information and Communications Technology for careers in data analysis and machine learning.

Objectives:

• Equip graduates with the skills and knowledge to analyze large datasets and extract meaningful insights.
• Develop expertise in Python, a popular data science language.
• Understand the ethical implications of AI and data analysis.
• Prepare graduates for careers in a variety of industries, including business, government, and research.

Description:

The AI&DA program consists of 32 weeks of intensive study, covering topics such as:

• Business mathematics and data analytics
• Data engineering
• Programming for data science
• Web analytics and business intelligence tools
• Enterprise data architecture
• Introduction to artificial intelligence
• Machine learning
• Artificial intelligence for management and ethical issues
• Indigenous Studies
• Capstone project
The program focuses on hands-on learning, with students working on real-world projects throughout the course. Graduates will be prepared for entry-level positions in data analysis, data science, and machine learning.

Outline:

Semester 1:

• ANLT-600 Business Mathematics and Data Analytics (3 credits): Estimating costs and benefits for process change, querying from existing data sources, outlining assumptions, developing cost benefits models, analyzing outcomes, separating assumptions from the model, developing flexible formulae.
• COMP-603 Programming for Data Science (3 credits): Python programming, data structures, visualization of real data, Boolean logic, control flow, loops, GIT usage.
• COMP-604 Web Analytics and Business Intelligence Tools (3 credits): Importance of business intelligence, reporting information effectively, modern BI tools.
• COMP-606 Machine Learning (3 credits): Applying algorithms, building and evaluating predictive models, tuning models, pre-processing data.
• INDG-600 Indigenous Studies (1 credit): Blanket Exercise, history of relationships between European settlers and Indigenous peoples, 94 Calls to Action of the Truth and Reconciliation Commission.
• PROJ-613 Capstone Project (3 credits): Planning and executing a major AI&DA project, group work, project management and monitoring, stakeholder communication.

Assessment:

Assessment methods include:

• Assignments and projects
• Quizzes and exams
• Presentations
• Capstone project
Grading criteria vary depending on the specific assessment method.

Teaching:

The program is taught by experienced faculty with expertise in data analysis, machine learning, and artificial intelligence. The teaching methods are varied and include:

• Lectures
• Tutorials
• Labs
• Group work
• Online learning
The program also offers unique learning opportunities such as:
• Guest lectures from industry experts
• Access to industry-standard software
• Opportunities to participate in research projects

Careers:

Graduates of the AI&DA program are prepared for a variety of careers in data analysis, data science, and machine learning. Some potential career paths include:

• Data analyst
• Data scientist
• Machine learning engineer
• AI specialist
• Business intelligence analyst
• Market research analyst
The program also prepares graduates for further study in related fields, such as computer science or data analytics.

Other:

• The program is offered on a full-time basis.
• The program is offered at both the Regina and Saskatoon campuses.
• The program is open to international students.