- About Us
- Faisal Beg – Algorithms to Advance Research in Medicine
- Yasutaka Furukawa – Smart Building Technologies to Enhance Living Spaces and Create Opportunities
- Mo Chen – AI to Create Safe and Practical Robotics
- Sheelagh Carpendale – Understanding Data Through Interaction and Visualization
- Innovation to Improve 3D Navigation
- Voice AI is Helping Shoppers Make Better Decisions
- Geographic Information Science Can Help Better Track COVID-19
- Deep Learning to Inform Medical Diagnoses
- Protecting Killer Whales from Marine Traffic
- Using Big Data to Boost Athletic Performance
- Machine Reading for Literary Texts
- Finding a Cure for HIV with Big Data
- Linked Data for Women's History
- How Big Data Can Combat Fake News
- Algorithms for Safer Streets
- Discovering Wilde Data
- Deep Blue Data
- Big Data Meets Big Impact
- Previous Next Big Question Fund Projects
- Data Fellowships
- Using Data
- Avoid and Detect
- Data For Good
- Artificial Intelligence at SFU
- Cybersecurity and Resilience
- Security and Resilience
- Gender Gap Tracker
- Upcoming Events
Data Fellowships: Data and AI
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.
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
- Data Exploration, Analysis, and Machine Learning
- Analytical Mindset and Business Understanding
- Solution Evaluation and Communication
- Data Collection and Management
Why choose SFU?
TAUGHT BY LEADING EXPERTS
Our instructors, who have decades of experience in both development and state-of-the-art big data and AI research, will teach you in-demand skills, approaches, concepts and tools.
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 virtual learning environment, enabling real-time feedback and encouraging you to build connections with your peers.
"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
I took SFU Data Fellowships in order 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
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 email@example.com.
Duration: 6 weeks
March 7-11 (8:30am - 12:30pm daily)
March 16 (11:30am - 1:30pm)
March 23 (11:30am - 1:30pm)
March 30 (11:30am - 1:30pm)
April 6 (11:30am - 1:30pm)
April 13 (11:30am - 1:30pm)
Register for Data Fellowships
Gain the knowledge and skills recruiters and organizations value.
PhD, Artificial Intelligence and Cognitive Science
Scientific Director, SFU’s Big Data Hub and Professor of Computing Science
MSc, Computing Science, Big Data Concentration
Big Data Developer, SFU's Research Computing Group
PhD, Computing Science
Limited-Term Lecturer, SFU's School of Computing Science
MSc Candidate, SFU’s School of Computing Science
Research Support, SFU’s Big Data Hub
PhD, Computing Science, Adjunct Professor, School of Engineering Science, Simon Fraser University
PhD Candidate, School of Computing Science
Research Assistant, SFU's Big Data Hub
PhD Candidate, School of Interactive Arts and Technology
Research Assistant, SFU's Big Data Hub
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 firstname.lastname@example.org
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 more than 25 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.