====== MA8701 Advanced statistical methods in inference and learning - Spring 2023 ======

Formal NTNU course description: [[https://www.ntnu.edu/studies/courses/MA8701#tab=omEmnet]] 

This is a phd course in statistics - and requires active participation. Teaching activities are physical, except some of the Part 4 activities.

**Course coordinator and lecturer**: [[https://www.ntnu.edu/employees/mette.langaas|Mette Langaas]]\\
**Lecturer**: [[https://www.nr.no/?q=employee-search&query=kjersti+aas| Kjersti Aas]] (Part 4) on explainable AI/interpretable machine learning\\

**Scheduled teaching:** 
  * Monday and Friday 10.15-12.00 in S21 (Sentralbygg 2, across from Smia), Gløshaugen. 
  * This will be active teaching with discussions and student contributions.
  * Office hours 9-10 before class on Mondays and Fridays in [[https://link.mazemap.com/BOiwsH7L|Mettes office, 1236, Sentralbygg 2]]

**Course parts:**

  * Part 1: Core concepts
  * Part 2: Shrinkage and regularization 
  * Part 3: Ensembles (of trees and other methods)
  * Part 4: Explainable AI
  * Part 5: Closing

**Evaluation**

The grade for this course is pass/fail evaluated with an individual oral exam.

To attend the exam you need to have done the following activities - all in groups (size 2-3):

  * Data analysis group project: data analysis short report with peer review followed by evaluation by lecturer 
  * Oral presentation of chosen/assigned scientific article or manuscript


**Course prerequisites:** 

  * TMA4267 Linear statistical models 
  * TMA4295 Statistical inference
  * TMA4300 Computer intensive statistical methods
  * TMA4315 Generalized linear models 
  * TMA4268 Statistical learning 

**Helpful knowledge**

  * TMA4180 Optimization 

**Programming/IT-knowledge**

  * Good programming skills in either R or Python.

====== Reference group ======

  * Philip Stanley Mostert
  * Jacob Daniel Benestad
  * Didrik Lindløv Sand

First meeting Friday 27.01 12.15, second meeting 20.03 12.15, last meeting 25.05 kl 10.15. Minutes from the meeting uploaded at Blackboard.