Certificate in Artificial Intelligence

Learn AI before AI learns you

Data is the new currency across a variety of different industries. More and more businesses are adopting artificial intelligence (AI) to unlock the incredible value of data, opening opportunities for those that are proficient in machine learning, deep and graphical networks, and reinforcement learning. Now is the time to learn AI and leverage those opportunities.

Engineering at Alberta has put our leading edge equipment and expertise behind a three module certificate program, extending our expertise to working professionals through the new Certificate in Artificial Intelligence program.


  • Online synchronous weekly classes
  • Three, six-week modules over 10 months
  • Classes on Fridays (3 pm to 5 pm) and Saturdays (9-11 and 12-2)
  • Experiential Learning
  • APEGA continuing professional development credits

Work and Learn

You can complete this certificate easily with limited time away from work. Each of the three, six-week courses is offered online. The synchronous virtual classes will be held on Friday afternoons and on Saturdays via Zoom.

Learn through Experience

Gain hands-on experience in practical applications of AI using Python coding language and Engineering at Alberta’s hardware to develop model AI algorithms and programs as well as neural network pathways to be tested with the faculty’s computational processing equipment. You will access resources available at the newly opened AI Hub, which  has already been working with small businesses to translate large data sets into more usable and valuable information.

Courses will focus on experiential learning using industry relevant projects. You will  work in and lead project teams in learning activities that are relevant and transferable to your current work.

Gain APEGA continuing professional development credit

This program qualifies for 108 continuing professional development hours in the ‘formal activity’ category of APEGA’s professional development requirement. 

Engineering at Alberta

We are one of the top five engineering schools in Canada, with more than 4,400 undergraduate students and 1,200 graduate students. And now we are developing new programs for the working professional. This is a place that uncovers the unknown. Where ideas take the stage and possibility runs the show. We train people to embrace curiosity, providing state-of-the-art facilities, award-winning faculty and support.

Admission Requirements

  • You have a post-secondary degree or diploma in computer science/engineering or other related program
  • You have an intermediate level of experience programming in Python
  • Knowledge of Jupyter Notebook is welcome



  1. Machine Learning Applications
  2. Applications with Deep and Graphical Networks
  3. Applications in Reinforcement Learning



Regular: $5,850

(please note cancellation policy below)



Overview (pdf)

Syllabus (pdf)


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Course Descriptions

AIE 1: Machine Learning Applications

This module offers an introduction to a variety of unsupervised and supervised methods of data processing. Learn different architecture configurations for predictive modeling, kernel methods, neural networks, and techniques for evaluation of model performance. You'll bring real-world problems from your own workplace, and use machine learning to solve them. With access to the state-of-the-art resources in the Faculty of Engineering, and leading researchers in the area, your learning will be hands-on and practical with application to industry.

AIE 2: Applications with Deep and Graphical Networks

Dive into Deep Learning methodology and begin to build neural networks. The module will cover subjects such as convolutional neural networks and their applications to images; recurrent network models for processing natural language and speech. It will also introduce networks representing probability distributions, in particular Bayesian and Markov networks, and their applications.

AIE 3: Reinforcement Learning Applications

An introduction to principles of reinforcement learning that include algorithms supporting action decision processes that optimize long-term performance. Topics include: dynamic programming, Q-learning, Monte Carlo reinforcement learning, and efficient algorithms for single- and multi-agent planning.


Cancellation Policy

  • Program sessions may be cancelled by FoE CPD up to 15 calendar days prior to the scheduled start date due to insufficient enrolment or other causes. In the event a program session is cancelled, participants will be offered a place in a future session of that program or in an equivalent program of the same duration. If no suitable session is available, participants will receive a full refund.
  • Registrants who provide notice of cancellation at least 15 days in advance of the start date for 2-5-day programs and 21 days in advance of the start date for 6+ day programs or certificates will receive a full refund.
  • Late cancellations from 2-5-day programs will be subject to an administration fee of $500.
  • Late cancellations from 6+ day programs or standalone modules within those programs will be subject to an administration fee of $1000.
  • Late cancellations from certificate programs or standalone modules within those programs will be subject to an administration fee of $2000.
  • Non-attendance will incur full seminar tuition cost. If you are unable to attend the program, your organization may name a replacement participant.
  • If possible, you should make travel arrangements after the cancellation deadline has passed. You may want to consider purchasing travel insurance if you have to book flights/trips ahead of the deadline for session cancellations.
  • FoE’s liability is limited to reimbursement of paid tuition fees. Fees, dates and speakers are subject to change.