A student's guide to COMP9418 at UNSW: what the course covers (Bayesian networks, exact and approximate inference, HMMs, learning), the Darwiche textbook, the open-book exam format, and free notes for every topic.
Masters of Statistics
2026-09-02
| # | Course Code | Title | Offered | Prerequisites | Term | Type | Textbook | Notes |
|---|---|---|---|---|---|---|---|---|
| 1. | COMP6713 | Natural Language Processing | T1 | MATH1081,9444 | 26T1 | Elective | na | |
| 2. | FINS5513 | Investments and Portfolio Selection | T1,2,3 | 8750 program | 26T1 | Elective | na | |
| 3. | FINS5536 | Fixed Income Securities and Interest Rate Derivatives | T2 | 5513 | 26T2 | Elective | na | pricing, hedging, risk management. options, futures and swaps (int rate derivs) |
| 4. | MATH5856 | Introduction to Statistics and Statistical Computations | T2 | 26T2 | Elective | na | recommended for 5905 | |
| 6. | MATH5960 | Bayesian Inference and Computation | T3 | 2801/2901 | 26T3 | Elective | ||
| 7. | MATH5825 | Measure, Integration and Probability | T3 | U5705 | 26T3 | Elective | na | implicit prereq for 5835 |
| 8. | MATH5905 | Statistical Inference | T1,2,3 | U5846,U5856 | 27T1 | Core | na | |
| 9. | COMP9518 | Advanced Machine Learning | T2 | 9517 | 27T2 | Elective | na | |
| 10. | MATH5845 | Time Series | T2 | 27T2 | Elective | na | ||
| 11. | MATH5855 | Multivariate Analysis | T3 | 27T3 | Elective | na | ||
| 12. | MATH5835 | Advanced Stochastic Processes | T1 | U5825 | 28T1 | Core | na | Difficult. Requires an understanding of Real Analysis and Measure Theory |
| 13. | MATH5806 | Applied Regression Analysis | T2 | 28T2 | Elective | na | splines, poisson / binomial regression | |
| 14. | MATH5925 | Project (12uoc) | T1,2,3 | 36UoC | 28T2 | Core | na |
course pages
Per-course write-ups — admin, textbooks, and links into my notes and solutions — for the courses I have completed:
- COMP9418 — Advanced Topics in Statistical Machine Learning (26T2)
- MATH5806 — Applied Regression Analysis (26T2)
new plan ATTACH
| term (tentative) | course code | course name | UoC |
|---|---|---|---|
| 27T1 | MATH5975 | Introduction to Stochastic Analysis | 6 |
| 27T1 | MATH5371 | Numerical Linear Algebra | 6 |
| 27T2 | COMP9418 | Advanced Machine Learning | 6 |
| 27T3 | MATH5960 | Bayesian Inference and Computation | 6 |
| 28T1 | FINS5513 | Investments and Portfolio Selection | 6 |
| 28T1 | MATH5905 | Statistical Inference | 6 |
| 28T2 | FINS5536 | Fixed Income Securities & Interest Rate Derivatives | 6 |
| 28T2 | MATH5835 | Advanced Stochastic Processes | 6 |
| 29T1 | MATH5845 | Time Series | 6 |
| 29T1 | MATH5925 | Project | 6 |
| 29T2 | MATH5825 | Measure, Integration and Probability | 6 |
| 29T2 | MATH5925 | Project | 6 |
rebellion plan
handbook: https://www.handbook.unsw.edu.au/postgraduate/programs/2026/8750?year=2026
| term (tentative) | course code | course name | UoC |
|---|---|---|---|
| 26T2 | COMP9418 | Advanced Machine Learning | 6 |
| 26T2 | FINS5513 | Investments and Portfolio Selection | 6 |
| 26T3 | FINS5535 | Derivatives and Risk Management Techniques | 6 |
| 26T3 | MATH5960 | Bayesian Inference and Computation | 6 |
| 27T1 | MATH5835 | Advanced Stochastic Processes | 6 |
| 27T1 | MATH5975 | Introduction to Stochastic Analysis | 6 |
| 27T2 | MATH5845 | Time Series | 6 |
| 27T2 | MATH5905 | Statistical Inference | 6 |
| 27T3 | MATH5825 | Measure, Integration and Probability | 6 |
| 27T3 | MATH5925 | Project | 6 |
| 28T1 | MATH5371 | Numerical Linear Algebra | 6 |
| 28T1 | MATH5925 | Project | 6 |
full-time 85 wam plan
handbook: https://www.handbook.unsw.edu.au/postgraduate/programs/2026/8750?year=2026
| term (tentative) | course code | course name | UoC |
|---|---|---|---|
| 26T2 | COMP9418 | Advanced Machine Learning | 6 |
| 26T2 | MATH5806 | Applied Regression Analysis | 6 |
| 26T3 | MATH5825 | Measure, Integration and Probability | 6 |
| 26T3 | MATH5960 | Bayesian Inference and Computation | 6 |
| 27T1 | MATH5835 | Advanced Stochastic Processes | 6 |
| 27T1 | MATH5975 | Introduction to Stochastic Analysis | 6 |
| 27T2 | MATH5845 | Time Series | 6 |
| 27T2 | MATH5905 | Statistical Inference | 6 |
| 27T3 | MATH5816 | Continuous Time Financial Modelling | 6 |
| 27T3 | MATH5005 | Project | 6 |
| 28T1 | MATH5371 | Numerical Linear Algebra | 6 |
| 28T1 | MATH5006 | Project | 6 |
Detecting Anomalies in the Dependence Structure of Multivariate Extremes.
| term | course code | course name | UoC |
|---|---|---|---|
| 26T2 | COMP9418 | Advanced Machine Learning | 6 |
| 26T2 | MATH5806 | Applied Regression Analysis | 6 |
| 26T3 | MATH5825 | Measure, Integration and Probability | 6 |
| 26T3 | Multivariate Analysis | 6 | |
| 26T3 | MATH5905 | Statistical Inference | 6 |
| 27T1 | MATH5835 | Advanced Stochastic Processes | 6 |
| 27T1 | Extreme Value Theory | 6 | |
| 27T1 | Survival Analysis | 6 | |
| 27T2 | MATH5845 | Time Series | 6 |
| 27T2 | Functional Analysis | 6 | |
| 27T2 | MATH5005 | Project A | 6 |
| 27T3 | MATH5006 | Project B | 6 |
| 27T3 | Bayesian Inference and Computation | 6 |
LambdaMind
The plan the λambda vault is built around (updated 2026-09-02). One swap on the previous table: Bayesian Inference and Computation moves forward to 26T3 and Multivariate Analysis takes its slot in 27T3. Measure theory stays in 26T3 because Advanced Stochastic Processes and Extreme Value Theory lean on it the following term; Statistical Inference stays because everything else assumes it.
Thesis intent (Project A/B, 27T2–27T3): fair ranking and exposure pricing on a live two-sided marketplace — a white-box decision network under a stated fairness-of-exposure floor, with the ranking policy’s own randomisation as the instrument for position bias. Co-supervision across Statistics and CSE is being arranged. The PhD direction after that is adversarial machine learning.
| term | course code | course name | UoC |
|---|---|---|---|
| 26T2 | COMP9418 | Advanced Machine Learning | 6 |
| 26T2 | MATH5806 | Applied Regression Analysis | 6 |
| 26T3 | MATH5825 | Measure, Integration and Probability | 6 |
| 26T3 | MATH5960 | Bayesian Inference and Computation | 6 |
| 26T3 | MATH5905 | Statistical Inference | 6 |
| 27T1 | MATH5835 | Advanced Stochastic Processes | 6 |
| 27T1 | MATH5805 | Extreme Value Theory | 6 |
| 27T1 | MATH5916 | Survival Analysis | 6 |
| 27T2 | MATH5845 | Time Series | 6 |
| 27T2 | MATH5605 | Functional Analysis | 6 |
| 27T2 | MATH5005 | Project A | 6 |
| 27T3 | MATH5006 | Project B | 6 |
| 27T3 | MATH5855 | Multivariate Analysis | 6 |
A student's guide to MATH5806 at UNSW: generalised linear models in R, the Dobson & Barnett textbook, assessment breakdown (quiz, R assignment, mid-session, final), plus free notes and fully worked GLM solutions.
Backlinks (3)
1. COMP9418 — Advanced Topics in Statistical Machine Learning at UNSW /blog/pgrad-unsw/comp9418/
A student's guide to COMP9418 at UNSW: what the course covers (Bayesian networks, exact and approximate inference, HMMs, learning), the Darwiche textbook, the open-book exam format, and free notes for every topic.
2. MATH5806 — Applied Regression Analysis at UNSW /blog/pgrad-unsw/math5806/
A student's guide to MATH5806 at UNSW: generalised linear models in R, the Dobson & Barnett textbook, assessment breakdown (quiz, R assignment, mid-session, final), plus free notes and fully worked GLM solutions.
3. Blog /blog/
welcome
this page is for my non-technical ramblings.
“If I had a world of my own, everything would be nonsense.” —The Hatter