Timetable

Content is arranged by blocks (single week of teaching content). These are scheduled for odd weeks in the University system.

There are five assessments (Assessment 1-3, Portfolio A-B), due in weeks 12,13,17 and 24.

Semester 1

• Week 1 (26th September)
  • 00 About
  • Block 01 Introduction
  • Assessment 0 Set
  • Portfolio 0 Set
• Week 3 (10th October)
  • Block 02 Regression and Statistical Testing
  • Assessment 0 Due (Thursday noon)
• Week 5 (24th October)
  • Block 03 Latent Structures, PCA, and Clustering
  • Portfolio 0 Due
  • Assessment 1 Set
  • Portfolio A Set
• Week 7 (7th November)
  • Block 04 Non-parametrics and Missing Data
• Week 9 (21st November)
  • Block 05 Supervised Learning and Ensembles
• Week 11 (5th December)
  • Block 06 Decision Trees and Random Forests
• Week 12
  • Assessment 1 Due (Wednesday noon)

Semester 2

• Week 13 (23rd January)
  • Block 07 Topic Models and Bayes
  • Portfolio A Due (Wednesday noon)
  • Portfolio B Set (Wednesday noon)
  • Assessment 2 Set
• Week 15 (6th February)
  • Block 08 Algorithms for Data Science
• Week 17 (20th Feb)
  • Block 09 Perceptions and Neural Networks
  • Assessment 2 Due
  • Assessment 3 Set
• Week 19 (6th March)
  • Block 10 Parallel Algorithms
• Week 21 (20th March)
  • Block 11 Parallel Infrastructure and Spark
• Week 23 (17th April)
  • Block 12 Ethics and Privacy
• Week 24
  • Portfolio B Due (Wednesday noon)
  • Assessment 3 Due (Wednesday noon)