Programme structure

The programme option Robotics and intelligent systems gives you the opportunity to choose a specialization in one, or more, of the topics: robotics systems, artificial intelligence or digital embedded systems. Theme for the Master's thesis is associated with advanced issues within the topics.

You choose courses in consultation with your supervisor and these will give you a solid theoretical basis for the completion of the Master's thesis. At least 30 credits must be from the list of core courses.

Structure for students admitted before autumn 2021.

Core courses

Autumn courses:

• IN4190 – Digital Signal Processing
• IN5200 – Advanced Digital System Design
• IN5490 – Advanced Topics in Artificial Intelligence for Intelligent Systems
• IN5520 – Digital Image Analysis
• TEK4030 – Control of Manipulators and Mobile Robots
• TEK5010 – Multi-Agent Systems
• TEK5020 – Pattern Recognition
• TEK5040 – Deep Learning for Autonomous Systems

Spring courses:

• IN5590 – Rapid Prototyping of Robotic Systems
• IN5400 – Machine Learning for Image Analysis
• IN5260 – Low Power IoT nodes
• FYS4240 – Data Acquisition and Control
• STK4900 – Statistical Methods and Applications
• TEK4050 – Stochastic systems
• TEK5030 – Computer Vision

 

Other recommended courses

Autumn courses

• Entrepreneurship courses (which courses will be updated)
• IN4110 – Problem Solving with High-Level Languages
• FYS4220 – Real Time and Embedded Data Systems
• MCT4045 – Interactive Music Systems (continued)
• MCT4047 – Music and Machine Learning (continued)

Spring courses

• IN4050 – Introduction to Artificial Intelligence and Machine Learning
• IN4160 – Digital system design
• IN4140 – Introduction to Robotics
• TEK5600 – Visualization of Scientific Data
• MUS4218 – Methodological topic: Cognitive musicology (discontinued)
• MNKOM4000 – Formidling og vitenskapsjournalistikk