Technical Learning
Dive into the foundations of applied machine learning (ML), decision trees, data cleaning, K-NN, regression and more.
Dive into the foundations of applied machine learning (ML), decision trees, data cleaning, K-NN, regression and more.
Learn techniques you can apply in game development, customer interaction, recommender systems, and across industries like health, finance, oil & gas and supply chain.
Modern businesses recognize the transformative power of AI but are also facing a severe shortage of skilled workers. The demand for AI and ML expertise is growing across all industries. Through the marriage of your domain expertise with technical ML skills, companies can gain competitive advantages.
We take a project-based and blended learning approach to training with lectures, programming labs and group work. Many of our technical training opportunities include capstone projects that conclude with feedback from a panel of experts and referrals for internships, apprenticeships and ML lead roles.
Gain technical skills and understanding at all stages of AI adoption.
Brainstorm ideas, learn foundational skills, understand use cases, and experience integrating and cleaning various data sources.
Learn data collection and cleaning, and how to prep data for ML.
Prepare for a proof-of-concept project, including implementing a chosen algorithm, testing for performance, and troubleshooting and optimizing the model.
Explore ethics, and gain insight into the translation of a business problem into an ML question.
Learn how to deploy an ML model, integrate it with legacy systems and establish an ML data pipeline.
Gain a deep understanding of the particular issues around ML at this stage of industry adoption.
Watch for and troubleshoot unexpected effects from a deployed ML system.
Gain experience with specific technical platforms and apply a broad range of ML models and techniques.
Learn how to translate academic research into applied commercial systems.
Foster an ability to work as part of an interdisciplinary team to advance targeted research and business objectives.
The AI Adoption Spectrum is foundational to our work. Learn more about how we work, and the role we can play in your personal AI adoption journey.
Certification
Modern businesses recognize the transformative power of AI but are also facing a severe shortage of skilled workers. This 13-week fully online course (6-9 hours per week) will help you prepare to meet the growing demand, combining your domain expertise with technical ML skills to unleash unlimited opportunities for your future!
Intake for the current session is now closed. Please check back soon for future dates.
Feb 23rd 2021
News
On January 28, Fellow and Canada CIFAR AI Chair at Amii Michael Bowling (Professor of Computing Science at the University of Alberta) presented "Hindsight Rationality: Alternatives to Nash" as the inaugural talk in the COMARL Seminar Series.
Feb 22nd 2021
News
On February 12, UAlberta Professor Denise Campbell-Scherer presented “Using Anthrocomplexity and Sensemaking to Understand and Mitigate the impacts of COVID-19: Opportunities for interdisciplinary collaboration”.
Feb 16th 2021
News
On February 5, UAlberta Computing Science alumna Karen Willsey presented AI in Action - The WeStretch Story.
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