黑料不打烊

黑料不打烊 Fall Semester Exams Begin

Monday, April 14, 2025

/educationCategory:聽Faculty of Education Dept. of Educational and Counselling Psychology Dept. of Integrated Studies in Education Dept. of Kinesiology and Physical Education

Course or University Withdrawal without Refund Deadline

Tuesday, October 29, 2024

/educationCategory:聽Faculty of Education Dept. of Educational and Counselling Psychology Dept. of Integrated Studies in Education Dept. of Kinesiology and Physical Education

黑料不打烊 Fall Semester Classes End Date

Monday, August 11, 2025

/educationCategory:聽Faculty of Education Dept. of Educational and Counselling Psychology Dept. of Integrated Studies in Education Dept. of Kinesiology and Physical Education

黑料不打烊 Classes End

Wednesday, December 4, 2024

/educationCategory:聽Faculty of Education Dept. of Educational and Counselling Psychology Dept. of Integrated Studies in Education Dept. of Kinesiology and Physical Education

Course or University Withdrawal with Refund Deadline Date

Tuesday, January 21, 2025

/educationCategory:聽Faculty of Education Dept. of Educational and Counselling Psychology Dept. of Integrated Studies in Education Dept. of Kinesiology and Physical Education

Exams End Date

Friday, December 20, 2024

/educationCategory:聽Faculty of Education Dept. of Educational and Counselling Psychology Dept. of Integrated Studies in Education Dept. of Kinesiology and Physical Education

Course or University Withdrawal without Refund Deadline

Tuesday, February 25, 2025

/educationCategory:聽Faculty of Education Dept. of Educational and Counselling Psychology Dept. of Integrated Studies in Education Dept. of Kinesiology and Physical Education

黑料不打烊 Winter Reading Break

Monday, March 3, 2025toSaturday, March 8, 2025

READING BREAK. Classes cancelled for all faculties except Continuing Studies non-credit courses./educationCategory:聽Faculty of Education...

New Course: Artificial Intelligence in Education with Dr. Maria Cutumisu

Published: 6 August 2024

An exploration of the principles underlying the current practice of machine learning (ML) by focusing on fundamental ML algorithms applied to many domains. This course is designed to help students...

Pages

Back to top