Due to COVID-19 concerns and policies, we have postponed this class until the Fall, exact dates to be determined.
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VECTOR INSTITUTE AI CERTIFICATE COURSES FOR INDUSTRY
Deep Learning I: Neural Networks and Supervised Learning
Available to
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Date: Mar 17 - May 5, 2020 (Classes run Tuesdays, 10 a.m. - 2 p.m.), final assignment due May 19, 2020
Location: Vector Institute, MaRS Building, 661 University Ave Suite 710, Toronto, ON M5G 1M1
Instructors:
FEES: Total Course Fee: $5,000
(A deposit of $250 will be collected upon registration. $4,750 will be invoiced upon course commencement.)
Must read:
Course Overview
The Deep Learning I: Neural Networks and Supervised Learning course provides an overview of the foundational ideas and recent advances in neural net algorithms with a focus on supervised learning. Created by
Who Should Attend
Available to
Learning Outcomes
At the end of this course participants will be able to:
Prerequisites
Course Load
Participants can expect to spend a total of 10-15 hours per week attending Lectures, Tutorials, Industry Discussions, and completing assignments.
Instructors
Course Outline & Schedule
Note that classes run Mar 17-May 5, 2020 with final assignment due May 19, 2020.
Week 1: Tuesday, Mar 17/20
10:00-12:00 Lecture: Introduction (Alireza Makhzani)
11:00-12:00 Lecture: Linear Models (Alireza Makhzani)
12:00-12:30 Lunch
12:30-1:00 Industry Discussion: Andrew Brown, CIBC
1:00-2:00 Tutorial: TA TBA
Week 2: Tuesday, Mar 24/20
10:00-11:00 Lecture: Multilayer Perceptrons (Alireza Makhzani)
11:00-12:00 Lecture: Backpropagation (Alireza Makhzani)
12:00-12:30 Lunch
12:30-1:00 Industry Discussion: Andrew Brown, CIBC
1:00-2:00 Tutorial: TA TBA
Week 3: Tuesday, Mar 31/20
10:00-11:00 Lecture: Distributed Representations (Mengye Ren)
11:00-12:00 Lecture: Automatic Differentiation (Mengye Ren)
12:00-12:30 Lunch
12:30-1:30 Tutorial: TA TBA
Week 4: Tuesday, Apr 7/10
10:00-12:00 Lecture: Optimization I (Mengye Ren)
11:00-12:00 Lecture: Optimization II (Mengye Ren)
12:00-12:30 Lunch
12:30-1:00 Industry Discussion: Andrew Brown, CIBC
1:00-2:00 Tutorial: TA TBA
Week 5: Tuesday, Apr 14/20
10:00-11:00 Lecture: Convolutional Networks (Mengye Ren)
11:00-12:00 Lecture: Image Classification (Mengye Ren)
12:00-12:30 Lunch
12:30-1:30 Tutorial: TA TBA
Week 6: Tuesday, Apr 21/20
10:00-11:00 Lecture: Optimizing the Input (Mengye Ren)
11:00-12:00 Lecture: Generalization (Mengye Ren)
12:00-12:30 Lunch
12:30-1:30 Tutorial: TA TBA
Week 7: Tuesday, Apr 28/20
10:00-11:00 Lecture: Recurrent Neural Nets (Mengye Ren)
11:00-12:00 Lecture: Exploding and Vanishing Gradients (Mengye Ren)
12:00-12:30 Lunch
12:30-1:30 Tutorial: TA TBA
Week 8: Tuesday, May 5/20
10:00-11:00 Lecture: Attention (Alireza Makhzani)
11:00-12:00 Lecture: Transformers (Alireza Makhzani)
12:00-12:30 Lunch
12:30-1:00 Industry Discussion: Andrew Brown, CIBC
1:00-2:00 Tutorial: TA TBA