Jump to Block: (About) 01 02 03 04 05 06 07 08 09 10 11 12 (Assessments)
Timetable
Content is arranged by blocks (single week of teaching content).
There are 3 summative assessments (Assessment 1-2 + Portfolio), plus a formative (non-assessed) assessment and portfolio.
Semester 1
- 00 About
- Week 1: Block 01 Introduction
- Assessment 0 Set
- Portfolio 0 Set
- Week 2: Block 02 Regression and Statistical Testing
- Week 3: Block 03 Latent Structures, PCA, and Clustering
- Assessment 0 Due (Wednesday noon)
- Portfolio 0 Due (Wednesday noon)
- Assessment 1 Set
- Portfolio Set
- Week 4: Block 04 Non-parametrics and Missing Data
- Week 5: Block 05 Supervised Learning and Ensembles
- Week 6: Block 06 Decision Trees and Random Forests
- Week 7: Block 07 Perceptrons and Neural Networks
- Assessment 1 Due (Wednesday noon - 8th November)
- Assessment 2 Set
- Week 8: Block 08 Topic Models and Bayesian Methods
- Week 9: Block 09 Algorithms for Data Science
- Week 10: Block 10 Parallel Algorithms
- Week 11: Block 11 Ethics and Privacy
- Week 12: Revision Week - Portfolio focus
- Assessment 2 Due (Wednesday noon - 13th December)
- During January Examination Period:
- Portfolio Due (Wednesday noon - 17th January)