Course - Artificial Intelligence Methods - TDT4171
Artificial Intelligence Methods
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About the course
Course content
This course is a continuation of TDT4136 Introduction to Artificial Intelligence and TDT4172 Introduction to Machine Learning. The three main ways of reasoning (rule-based, model-based, and case-based), will be discussed, with most focus given to model-based reasoning. In particular, we work with reasoning based with uncertain and/or partly missing information. The reasoning frameworks that are most prominent in this part of the course are Bayesian networks and decision graphs.Thereafter, we discuss modern techniques for machine learning.
Learning outcome
Knowledge:
- General principles for artificial intelligence (AI)
- Efficient representation of uncertain knowledge
- Decision making principles
- Learning/adaptive systems.
Skills:
- Assess different frameworks for AI in given contexts
- Build systems that realises aspects of intelligent behaviour in computer systems.
General competence:
- Know AI's basis taken from mathematics, logic and cognitive sciences.
Learning methods and activities
Lectures, self study and exercises.
Compulsory assignments
- Mandatory assignments
Further on evaluation
A number of assignments are given out during the semester. A number of these must be passed to be eligible for exam. Details will be given at the start of the course.
The written exam will be given in English only.
If there is a re-sit examination, the examination form may change from written to oral.
Recommended previous knowledge
- TDT4136 Introduction to Artificial Intelligence, or equivalent.
- TMA4240 Statistics or similar
- TDT4172 Introduction to Machine Learning or similar
- Programming experience, e.g., TDT4109 - Information Technology, Introduction
Course materials
- Stuart Russel, Peter Norvig: Artificial Intelligence. A Modern Approach, Fourth Edition, Pearson, 2020.
- Ian Goodfellow and Yoshua Bengio and Aaron Courville: Deep Learning, MIT Press, 2016.
Any additional material will be distributed through the course's webpage.
Credit reductions
| Course code | Reduction | From |
|---|---|---|
| IT2702 | 3.7 sp | Autumn 2007 |
| IT272 | 3.7 sp | Autumn 2007 |
| MNFIT272 | 3.7 sp | Autumn 2007 |
| TDT4170 | 3.7 sp | Autumn 2007 |
| SIF8031 | 3.7 sp | Autumn 2007 |
| IT3704 | 3.7 sp | Autumn 2008 |
| MNFIT374 | 3.7 sp | Autumn 2008 |
| MNFIT374 | 3.7 sp | Autumn 2008 |
Subject areas
- Computer Systems
- Informatics
Contact information
Course coordinator
Department with academic responsibility
Examination
Examination
Ordinary examination - Spring 2025
School exam
The specified room can be changed and the final location will be ready no later than 3 days before the exam. You can find your room location on Studentweb.