9:00 AM: Registration & Refreshments

9:30 AM: Kick Off & Keynote

  • David Ferris - Senior Product Manager, Jobber | Some great and guaranteed ways to ensure your software fails

10:45 AM: Workshops - Six Sessions to Choose From! Beginner and advanced sessions available.

  • Amii is bringing their best and brightest for workshops on Machine Learning, Reinforcement Learning, and Natural Language Processing. 

  • Scope AR are industry leaders in augmented reality, working with folks like NASA (yes, that NASA), Toyota, and Microsoft. Join in workshops with team members building product that are shaping the future of the industry. 

  • Darkhorse Analytics is joining us to share ways you can use data and visualizations to shape decisions, improve products and processes, and captivate audiences. Don't miss a chance to hear from Eugene Chen, CTO and Director.  

  • MacEwan University brings UX expertise from the Bachelor of Design program to DevCon. Level-up your design knowledge from dedicated faculty members. 

12:00 PM: Lunch

12:45 PM: Keynote - How To Get Hired Panel

2:15 PM: Workshops - Check out the session descriptions!

3:15 PM: Coffee Break

3:45 PM: Keynote

5:00 PM: Company Mixer & Reception 

7:00 PM: Thanks & See You Next Year! 

The 2019 Student Developer Conference is presented in partnership with

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In the past we've had speakers from companies like Apple, AirBnB and Jobber! This year, more keynoters will inspire you with their personal stories, advice for students and recent graduates, and lively Q & A sessions.


We know that you already have a boatload of assignments to tackle for school. In our hands-on workshops you'll gain the skills required to impress and connect with a company as well as tangible ways to hit-the-ground running when you hired.  More workshop descriptions to come!

Beginner's Guide to Machine Learning | Tara Petrie & Talat Iqbal Syed - Amii

The Beginner’s Guide to Machine Learning is exactly that: it provides an introduction to machine learning. It will outline different approaches to machine learning and provide an overview of the intuition for several techniques used in supervised and unsupervised learning.

Tara (MSc) is a Machine Learning Educator for Amii, working to enhance machine intelligence knowledge for businesses and individuals. She received her master of science degree in mathematics from Simon Fraser University with a focus on discrete math and combinatorics. Tara is driven by the joy of sharing math and science with others.

Talat is an Applied Machine Learning Scientist at Amii, working with the applied team to translate the business problems into machine learning problems and address them. Talat has been working with Amii since 2015, starting with the Social Network Analysis project and moving into the Data Science team. He received his master of science degree in Computing Science from University of Alberta with his thesis focussed on unsupervised learning techniques. His research area interests lie in the domain of Natural Language Inference & Understanding and explainable AI. Before joining Amii, he worked with the Business Intelligence team for one of the largest telecom providers in North America.

Reinforcement Learning (without the math!) | Dr. Patrick Pilarski

Ever wonder how machines might learn through trial and error to interact with the world around them, but were scared off by all the fancy math and convergence proofs? Me too! This session will introduce key ideas from machine intelligence and reinforcement learning in an accessible, hands-on fashion. You will leave with an understanding of how a machine can learn to make predictions, take actions, and adapt to a changing environment of signals and data.

Patrick is a Canada Research Chair in Machine Intelligence for Rehabilitation at the University of Alberta, and an Associate Professor in the Division of Physical Medicine and Rehabilitation, Department of Medicine. Dr. Pilarski is a Fellow of the Alberta Machine Intelligence Institute (Amii) and principal investigator with the Reinforcement Learning and Artificial Intelligence Laboratory (RLAI). Dr. Pilarski received the B.ASc. in Electrical Engineering from the University of British Columbia in 2004, the Ph.D. in Electrical and Computer Engineering from the University of Alberta in 2009, and completed his postdoctoral training in computing science with Dr. Richard S. Sutton at the University of Alberta. Dr. Pilarski's research interests include reinforcement learning, real-time machine learning, human-machine interaction, rehabilitation technology, and assistive robotics. He leads the Amii Adaptive Prosthetics Program—an interdisciplinary initiative focused on creating intelligent artificial limbs to restore and extend abilities for people with amputations. As part of this research, Dr. Pilarski explores new machine learning techniques for sensorimotor control and prediction, including methods for human-device interaction and communication, long-term control adaptation, and patient-specific device optimization. He has also pioneered techniques for rapid cancer and pathogen screening through work on biomedical pattern recognition, robotic micro-manipulation of medical samples, and hand-held diagnostic devices. Dr. Pilarski is the author or co-author of more than 70 peer-reviewed articles, a Senior Member of the IEEE, and is currently supported by provincial, national, and international research grants.

Getting Started with Natural Language Processing | Luke Kumar

A broad overview of natural language processing techniques. We'll be introducing some symbolic and statistical techniques that have been used and are being used currently in the NLP domain. We'll spend more time on the machine learning perspective approaching NLP problems with some hands-on use cases. 

Luke Kumar is a Machine Learning Scientist at Amii and holds a master's degree in computing science from the University of Alberta. He has lead several machine learning projects in varies business domains during his time with Amii. 

Prior to joining Amii, Luke worked in a Canadian company on algorithms to detect online fraud transactions with high volume data. He has also worked in one of the LSE of Group companies on machine learning techniques to detect fraudulent activity in capital markets.

He has co-authored academic publications on machine learning applications in clinical oncology and software energy consumption.

Past Workshop Highlights

  • Version Control 

  • Lean Canvas Model

  • Game and Story Development

  • Web Development 

  • Design for Developers

  • Introduction to Machine Learning


One of the best parts about Student DevCon is your chance to connect directly with the CTOs and Dev Teams from  from some of Canada's fastest growing tech companies.

Getting hired & being a successful new team member takes a lot of work and preparation:

  • Get experience building and showing your work

  • Meet the people who work at the companies and learn as much as you can

  • Participate in the community: hackathons, hack days, meetups and more

Student DevCon is a great chance to kick-start your interaction with startup teams!


Join your new friends as socials throughout the day. Your registration includes: 

  • Light Breakfast 

  • Snack & Coffee Breaks

  • Job Mixer