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

T550021101

Course Title

Tools of Artificial intelligence

ECTS value

5

Internal Course Code

RMAI2

Responsible study board

Academic Study Board of the Faculty of Engineering

Administrative Unit

Mærsk McKinney Møller Instituttet

Date of Approval

27-09-2022

Course Responsible

Name Email Department
Kamilla Juel Sørensen kjs@tek.sdu.dk TEK Uddannelseskoordinering og -support
Preben Hagh Strunge Holm prebenh@mmmi.sdu.dk SDU Robotics

Teachers

Name Email Department City
Xiaofeng Xiong xizi@mmmi.sdu.dk Mærsk Mc-Kinney Møller Instituttet

Programme Secretary

Name Email Department City
Susanne Bech Fogtmann sfo@tek.sdu.dk TEK Uddannelseskoordinering og -support

Offered in

Odense

Level

Master

Offered in

Spring

Duration

1 semester

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

Lectures and exercises

Number of lessons

48 hours per semester

Teaching language

English

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
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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

Studieforløb