School of Information and Communications Technology

Artificial Intelligence and Data Analytics

Post-Graduate Certificate
Artificial Intelligence and Data Analytics

Program Overview

The goal of the program is to prepare internationally-educated graduates with degrees in information and communications technology for the fields of data analysis and machine learning. Humans have always wanted to better understand the massive amounts of currently available and newly gathered data and what that means for future potential.

Artificial Intelligence and Data Analytics is the power to analyze and learn about large amounts of data from multiple sources and detect patterns to make future trend predictions. Business and industry benefits from predictive analytics to make decisions about production, marketing and development.

You will study:

  • cost and benefit estimation for process change
  • conversion of business questions into data mining problems
  • enterprise data architecture and associated technologies
  • strategies to leverage the popular data science language Python
  • importance of business intelligence to the modern enterprise
  • application of artificial intelligence (AI) application programming interfaces (APIs) to business applications
  • application of algorithms to make predictions that form the foundation of machine learning
  • ethical issues surrounding big data
  • emerging application of AI to common business areas

Length and Start Date

Start Date(s):

September and January (Regina and Saskatoon)


Length: 32 weeks

Locations

  • Regina
  • Saskatoon

Admissions

Admission Requirements

Admission Method

First Qualified/First Admitted

The First Qualified/First Admitted (FQFA) process is used for the majority of Saskatchewan Polytechnic programs. When we determine that you meet the program's admission requirements, you will be offered admission based on the date you fully qualify for the program. The earlier you provide the appropriate documents and information that qualify you for admission to the next intake, the earlier you might begin your studies. Your application, once qualified, is always considered for the next intake. 

Applicants to programs with multiple intakes in an academic year remain in the application pool until the last intake for that academic year has begun. Programs using the FQFA process receive applications year round and maintain an application pool for each academic year. Qualified applicants who are not offered a seat must reapply for the next academic year. 

Sponsored programs or programs targeted to specific groups do not accept applications year round or maintain an application pool.

See Admission Processes for more information about this method of admission.

Tuition and Fees

Estimates are based on current rates and are subject to change. Amounts for a program may vary by campus. Totals shown here include all mandatory fees as well as approximate cost for books and supplies. Visit the Tuition and Fees web page for a complete breakdown of tuition and fees for this program.

 

2022/23 Academic Year

$11,070

This program is Bring Your Own Device (BYOD). Students are required to bring their own laptop to class daily. The minimum requirements for this device are:

  • Intel I5
  • 16GB memory
  • 256GB HD
  • Windows (not MAC)

International Students

View tuition rates for international students.

Courses

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Semester 1

Code
Name/Description
Credits
 
ANLT 600
Business Mathematics and Data Analytics
3
Show course details
You will learn the essential skill of estimating costs and benefits for a process change. Your studies will include the development of theoretical knowledge and practical skills in these areas: querying from existing data sources, outlining assumptions, developing cost benefits models, analyzing outcomes over multiple years, separating assumptions from the model, and developing flexible formulae. A component of your studies will include an introduction to relational databases and advanced use of spreadsheet software.
Credit Units: 3
Course Hours: 45.0
Potential Learning Method(s): Lecture/Lab, Online
CDBM 602
Data Engineering
3
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You will study the conversion of business questions into data mining problems. You will identify sources of an organization’s data. You will use strategies to transform that data into a meaningful format for data mining which will involve you developing an understanding of data modeling and transformation.
Credit Units: 3
Course Hours: 45.0
Potential Learning Method(s): Lecture/Lab, Online
COMP 603
Programming for Data Science
3
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You will study strategies to leverage the popular data science language Python. You will perform visualization of real data and become acquainted with data structures such as the dictionary and the DataFrame. You will become familiar with key concepts such as Boolean logic, control flow, and loops and use GIT (open source version control system), to perform updates and manage the versions of your source code.
Credit Units: 3
Course Hours: 45.0
Potential Learning Method(s): Lecture/Lab, Online
COMP 604
Web Analytics and Business Intelligence Tools
3
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You will study the importance of business intelligence to the modern enterprise. You will study methods to report information effectively based on audience characteristics by leveraging modern business intelligence (BI) tools.
Credit Units: 3
Course Hours: 45.0
Potential Learning Method(s): Lecture/Lab, Online
TCOM 600
Business Technology Communications
3
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You will learn how to manage communication in a business environment using best practices and common software tools. You will learn how to produce effective content delivered with appropriate tools.
Credit Units: 3
Course Hours: 45.0
Potential Learning Method(s): Lecture/Theory, Online
Total semester credits: 15

Semester 2

Code
Name/Description
Credits
 
CDBM 603
Enterprise Data Architecture
3
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You will study enterprise data architecture and associated technologies. Your studies will include the fundamentals of relational data models and a discussion of the problems of redundancy and fragmentation. You will study the role of non-relational data models within organizations. Your studies will include data solution approaches such as data warehouses, data marts, data lakes and decentralized data models for micro services.
Credit Units: 3
Course Hours: 45.0
Prerequisites(s): CDBM 602
Potential Learning Method(s): Lecture/Lab, Online
COMP 605
Introduction to Artificial Intelligence
3
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You will study the application of artificial intelligence (AI) application programming interfaces (APIs) to business applications. You will use AI technology to augment and automate business processes. You will implement common AI applications including image recognition, sentiment analysis, and product recommendations.
Credit Units: 3
Course Hours: 45.0
Prerequisites(s): COMP 603
Potential Learning Method(s): Lecture/Lab, Online
COMP 606
Machine Learning
3
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You will study the application of algorithms and make predictions which form the foundation of machine learning. Your studies will include these ideas in machine learning: building and evaluating predictive models, tuning these models for optimal performance, and preprocessing data for better results.
Credit Units: 3
Course Hours: 45.0
Prerequisites(s): COMP 603
Potential Learning Method(s): Lecture/Lab, Online
COMP 607
Artificial Intelligence for Management and Ethical Issues
3
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You will learn the ethical issues of artificial intelligence as well as the role of professionalism and the ethical organization for the responsible execution of AI application. You will also learn the fundamentals of operations management, managing AI decision making, and strategic planning as it pertains to AI technology.
Credit Units: 3
Course Hours: 45.0
Potential Learning Method(s): Lecture/Lab, Online
PROJ 613
Capstone Project
3
Show course details
You will learn how to work in a group to plan and execute a major Artificial intelligence and Data analytics project. You will manage and monitor the project and produce documentation to communicate effectively with your stakeholders.
Credit Units: 3
Course Hours: 45.0
Potential Learning Method(s): Lecture/Lab, Online
Total semester credits: 15

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