YORK UNIVERSITY TORONTO – SUMMER SCHOOL 2020admin February 19, 2020 0 COMMENTS
Deadline: 9 March 2020
Open to: senior undergraduate students that have a background in Computer Science, Math, Engineering, Psychology, and Data Visualization
Venue: 19-22 May 2020, Toronto, Canada
The multi-institutional, interdisciplinary CREATE Program in Data Analytics and Visualization (DAV) at York University in Toronto offers an undergraduate summer school on big data science. This is a 4-day event (19-22 May 2020) is intended mainly for students who are planning to apply to graduate school in late 2020, and are interested in investigating interdisciplinary research aspects of the big data science.
The event includes talks by CREATE DAV faculty and industry experts on current research topics in big data science, as well as hands-on experience in York and OCAD U laboratories. The curriculum reflects the wide range of research areas at CREATE DAV, which includes research on machine learning, data mining, signal processing, computer vision, image processing, computer graphics, virtual human modeling, serious games, natural language processing, human perception & cognition, visualization & design.
Anyone with a background in Computer Science, Math, Engineering or Psychology and a strong interest in pursuing graduate studies in the subject is encouraged to apply. Even though admission is competitive, with most of their attendees having a GPA’s in the A range, students that don’t have exceptional grades but have other strengths, such as laboratory experience or excellent quantitative skills are encouraged to apply.
Applicants from all over the world are accepted, however the program covers only a portion of the travel expenses (up to USD 980), if the cost of travel exceed allocated amount, the applicant will be responsible for paying the remainder of their travel expenses. All applicants will have available on-campus accommodation which includes meals (attendees can modify their meals based on their allergies and dietary restrictions).