SFU Data Fellowships: AI Essentials

Course Overview

Learn foundational data science and AI skills that can be directly applied to your work and organization. Taught by AI experts at Simon Fraser University.

Live, Virtual Sessions

This online course is designed by leading data science and AI experts at Simon Fraser University. It is taught live by an experienced team of educators and researchers.

Learn From Experts

Our SFU instructors have decades of experience teaching and consulting for industry and government.

Real Outcomes

Work on your own business problems or a real world data problem from an SFU partner organization and build your industry revelant portfolio.

Build Your Network

Throughout the course, our instructors will provide hands-on guidance with the course material, as well as answer any career related questions. You will still be able to contact our instructors after the course ends in case you would like to connect further.

"I cannot overstate how well Data Fellowships has addressed both the technical and ethical aspects of AI and machine learning. I would absolutely recommend this workshop, especially to those without technical training in computer science."

-Camylle Lanteigne, Montreal AI Ethics Institute

Schedule

Pacific Time

July 4-8 (8:30am - 12:30pm daily)

Apply for a Grant

Qualified applicants can receive up to $1000 off this workshop. Once you apply, a member of SFU will reach out within 2 business days with your discount code.

Apply now

Did you know your organization may be able to cover the cost of this training program through a tuition reimbursement? If you need additional information to submit to your organization, email us at sfu_bigdata@sfu.ca

Who is this for?

• You are interested in switching or expanding your career in the data science and AI fields.
• You want to learn practical and application-focused material that can be applied to your work immediately.
• You want to improve your data science and AI skills and apply more data rigorous methods or auomated processes to your job.
• You are interested in gaining more industry relevant technical skills.

What You Will Learn

• Data Project Workflow and Foundations

• Analytical Mindset and Business Understanding

• Data Collection and Management

• Data Exploration, Analysis, and Machine Learning

• Solution Evaluation and Communication

Course Syllabus

Download syllabus

Why Choose SFU?

Taught By Leading Big Data and AI Experts

Our instructors, who have decades of experience in both development and state-of-the-art research, will teach you in-demand skills, approaches, concepts and tools.

Experiential Learning

Gain hands-on experience working on complex data science problems, ensuring the knowledge you gained in this course can be directly applied to the real-world.

Get Real-Time Feedback

This course is taught in a live learning environment, enabling real-time feedback and encouraging you to build connections with your peers.

Testimonial

"I took SFU Data Fellowships to learn more about machine learning methods. My research is currently focusing on the production and transformation of scandals in news media, and this course will help me expand the range of analytical methods I can use to analyse large data-sets of news articles. The lectures were excellent, providing solid introductions to machine learning concepts and real-world applications. I would absolutely recommend this course as it is well-designed and taught by a professional and skilled team committed to creating a positive learning environment for all skill levels."

- Colette Colligan, Professor of English, SFU

"I would highly reccomend this training program. It helped me learn more about AI and machine learning and sharpened my critical insight into the applications of algorithms as the knowledge is essential for those interested in digital methods."

- Dilli Bikram Edingo, Ph.D. candidate, York University

Instructors

Fred Popowich

PhD, Artificial Intelligence and Cognitive Science

Scientific Director, SFU’s Big Data Hub and Professor of Computing Science

Jillian Anderson

MSc, Computing Science, Big Data Concentration

Big Data Developer, SFU's Research Computing Group

Steven Bergner

PhD, Computing Science

Limited-Term Lecturer, SFU's School of Computing Science

Stephen Makonin

PhD, Computing Science,

Adjunct Professor, School of Engineering Science, Simon Fraser University

Ishan Sahay,

MSc, Computing Science

Big Data Consultant, SFU's Big Data Hub

Paige Tuttosi

PhD Candidate, School of Computing Science

Research Assistant, SFU's Big Data Hub

Prerequisites

Participants are not required to have previous knowledge of Python but some experience in coding would be beneficial. This course is designed to accommodate people with different levels of programming knowledge, and you will gain value regardless of your previous coding experience.

If you'd like to discuss with our team about whether you have the prerequisites to gain value from this course, please email sfu_bigdata@sfu.ca.

Questions?

Please contact sfu_bigdata@sfu.ca if you have any questions.

FAQ

Will I receive SFU credit for this course?

This is a non-credit course for which you will receive a Certificate of Completion.

Can I take this course at my own pace?

This course offers a live, structured learning environment with learning objectives and activities for each day. You will need to be available during the designated class times.

What is the refund policy?

There are no refunds offered for this workshop, however you may transfer your seat to another person free of charge. For questions about seat transfers please contact sfu_bigdata@sfu.ca

What is SFU's Big Data Hub?

Simon Fraser University leverages the power of big data so Canada can lead in a digital world. With over a decade of leadership in the big data field, SFU’s Big Data Hub engages with our partners to fill critical talent shortages, generate new knowledge and contribute to an innovative economy. We connect government, industry and the community to deliver data-driven solutions to challenging problems. With 24 governmental partners and over 100 companies actively engaged, we are empowering people to use data for impact and social good to solve global challenges and transform society.