Tools of Artificial intelligence
Academic Study Board of the Faculty of Engineering
Teaching language: English
EKA: T550021102
Censorship: Second examiner: External
Grading: 7-point grading scale
Offered in: Odense
Offered in: Spring
Level: Master
Course ID: T550021101
ECTS value: 5
Date of Approval: 27-09-2022
Duration: 1 semester
Version: Approved - active
Course ID
Course Title
ECTS value
5
Internal Course Code
Responsible study board
Administrative Unit
Date of Approval
Course Responsible
Name | Department | |
---|---|---|
Kamilla Juel Sørensen | kjs@tek.sdu.dk | TEK Uddannelseskoordinering og -support |
Preben Hagh Strunge Holm | prebenh@mmmi.sdu.dk | SDU Robotics |
Teachers
Programme Secretary
Name | Department | City | |
---|---|---|---|
Susanne Bech Fogtmann | sfo@tek.sdu.dk | TEK Uddannelseskoordinering og -support |
Offered in
Level
Offered in
Duration
Recommended prerequisites
It is recommended that the student has followed the 1st semester course Introduction to Artificial Intelligence (AI1).
Basic object oriented programming knowledge is recommended.
Learning objectives - Knowledge
- understanding of basic machine learning techniques: neural networks, genetic algorithms and reinforcement learning
- understanding of representational techniques appropriate to the above learning methods
- understanding of the experimental challenges and demands of the machine learning approaches referred to above
Learning objectives - Skills
- able to implement, debug and deploy the AI techniques taught in new situations
- able to devise suitable representations of data for chosen machine learning techniques
- able to test, evaluate and document the performance of chosen machine learning techniques using suitable correct methodologies
- able to write a straightforward experimental scientific paper documenting a comparison experiment
Learning objectives - Competences
- can identify robotic problems where machine learning techniques could be applied
- can select appropriate techniques from the toolbox of possibilities
- able to characterise a new AI technique in terms of scope and type (unsupervised, semi-supervised or supervised)
- can evaluate reported applications of machine learning techniques in terms of results and methodology
URL for Skemaplan
Teaching Method
Number of lessons
48 hours per semester
Teaching language
Examination regulations
Exam regulations
Name
Exam regulations
Examination is held
By the end of the semester
Tests
Exam
EKA
T550021102
Name
Exam
Description
Individual written report based on project submitted in the end of the semester.
Form of examination
Compulsory assignment
Censorship
Second examiner: External
Grading
7-point grading scale
Identification
Student Identification Card - Exam number
Language
English
ECTS value
5
Additional exam information
The form of examination in the re-examination is the same as in the ordinary examination.
Courses offered
Offer period | Offer type | Profile | Education | Semester |
---|---|---|---|---|
Spring 2024 | Optional | MSc in Physics and Technology, 2023 | Master of Science in Engineering (Physics and Technology) | Odense | |
Spring 2024 | Optional | MSc in Physics and Technology, 2022 | Master of Science in Engineering (Physics and Technology) | Odense | |
Spring 2024 | Optional | MSc in Electronics, 2022 | MSc Electronics, Odense | Master of Science in Engineering (Electronics) | Odense | |
Spring 2024 | Optional | Bachelor i spiludvikling og læringsteknologi, optag 2023 | Bachelor of Science in Engineering (Game Development and Learning Technology) | Bachelor of Science in Engineering (Game Development and Learning Technology) | Odense | |
Spring 2024 | Optional | Bachelor i spiludvikling og læringsteknologi, optag 2022 | Bachelor of Science in Engineering (Game Development and Learning Technology) | Bachelor of Science in Engineering (Game Development and Learning Technology) | Odense | |
Spring 2024 | Optional | Bachelor i spiludvikling og læringsteknologi, optag 2021 | Bachelor of Science in Engineering (Game Development and Learning Technology) | Bachelor of Science in Engineering (Game Development and Learning Technology) | Odense | |
Spring 2024 | Optional | Bachelor i fysik og teknologi, optag 2022 | Bachelor of Science in Engineering (Physics and Technology) | Odense | |
Spring 2024 | Optional | Bachelor i fysik og teknologi, optag 2021 | Bachelor of Science in Engineering (Physics and Technology) | Odense | |
Spring 2024 | Optional | Bachelor i fysik og teknologi, optag 2023 | Bachelor of Science in Engineering (Physics and Technology) | Odense | |
Spring 2024 | Mandatory | MSc in Robot Systems, 2022, Advanced Robotics Technology (ART) | Master of Science in Engineering (Robot Systems) | Odense | 2 |
Spring 2024 | Mandatory | MSc in Robot Systems, 2022, Drones and Autonomous Systems (DAS) | Master of Science in Engineering (Robot Systems) | Odense | 2 |
Spring 2024 | Mandatory | MSc in Robot Systems, 2023, Advanced Robotics Technology (ART) | Master of Science in Engineering (Robot Systems) | Odense | 2 |
Spring 2024 | Mandatory | MSc in Robot Systems, 2023, Drones and Autonomous Systems (DAS) | Master of Science in Engineering (Robot Systems) | Odense | 2 |