- 09:00 - Course Introduction
- 10:00 - Epistemology and lessons from the past
- 12:00 - Lunch
- 13:00 - Installation time and troubleshooting.
- 14:00 - Git and Github
- 17:00 - Dismissal
- 09:00 - Python for Data Analysis
- 12:00 - Lunch
- 13:00 - Using and building Containers
- 16:30 - Assessment 1
- 17:00 - Dismissal
- 18:00 - Optional social event
- 09:00 - Standards for project management and organization
- 12:00 - Lunch
- 13:00 - Guest Lecture on Binder
- 14:00 - High-Performance Computing and Compute Canada
- 17:00 - Dismissal
- 09:00 - Data visualization
- 10:00 - Multivariate statistics and matrix factorizations
- 12:00 - Lunch
- 13:00 - Guest Lecture on estimation of connectivity
- 14:00 - Classical machine learning
- 17:00 - Dismissal
- 09:00 - Introduction to Deep Learning
- 12:00 - Lunch
- 13:00 - Review Session
- 16:00 - Assessment 2
- 17:00 - Dismissal