Recommended prerequisite for participation in
the module
The module is based on knowledge achieved in the modules Linear
algebra, Calculus, Data structures and algorithms, Real-time
systems and programming languages.
Content, progress and pedagogy of the
module
Learning objectives
Knowledge
- Have knowledge about what encompasses artificial intelligence
(AI) and its main applications
- Have knowledge about the basic algorithms and heuristics used
for searching in graphs such as shortest path, A* and the
travelling salesman problem
- Have knowledge about optimisation techniques such as gradient
based methods for convex functions and metaheuristic methods
- Have knowledge about the concepts of supervised and
unsupervised machine learning techniques, about perceptron learning
and multilayer perceptron learning for classification
- Have knowledge about crisp logic systems and knowledge
representation
- Have knowledge about image processing and computer vision
algorithms
Skills
- Be able to design and implement AI based algorithms and
heuristics for searching, optimisation or knowledge representation
in a modern computer language such as Python or C++
- Be able to develop computer programs using libraries to
implement machine learning based systems for specific
applications
- Be able to design AI based computer programs for computer
vision and reasoning using 1st order logic
Competences
- Independently be able to apply AI to solve problems in robotics
and computer vision
- Independently develop an AI based system solutions for a
specific application domain
- Have a fundamental understanding of the techniques used in
AI
Type of instruction
Lectures with exercises, possibly supplemented with e-learning
as stated in § 17 in the BSc curriculum and §18 in the BE
curriculum.
Extent and expected workload
Since it is a 5 ECTS project module, the work load is expected
to be 150 hours for the student.
Exam
Exams
Name of exam | Introduction to Artificial Intelligence |
Type of exam | Written or oral exam |
ECTS | 5 |
Assessment | 7-point grading scale |
Type of grading | Internal examination |
Criteria of assessment | The criteria of assessment are stated in the Examination
Policies and Procedures |