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.
Requirements for course selection
There are different requirements of core courses for short and long master's thesis. Core courses are the most fundamental and specialized courses for your programme option.
- For the long thesis (60 ECT), you must choose a minimum of 30 ECT core courses
- For the short thesis (30 ECT), you must choose a minimum of 45 ECT core courses. You write the master's thesis in your final semester.
During the first semester, it is advisable to take core courses to ensure that you meet the minimum requirements. Once you have a supervisor, you choose the remaining master's courses together.
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 (discontinued)
- 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 (continued)
- IN5260 – Low Power IoT nodes
- FYS4240 – Data Acquisition and Control
- STK4900 – Statistical Methods and Applications
- TEK4050 – Stochastic Systems
- TEK5030 – Computer Vision
Other recommended courses (can't fullfill requirements regarding core courses)
Autumn courses
- Entrepreneurship courses (which courses will be updated)
- FYS4220 – Real Time and Embedded Data Systems
- MCT4054 – Interactive Music Systems
- IN4110 – Problem Solving with High-Level Languages
- IN5310 – Advanced Deep Learning for Image Analysis
Spring courses
- IN4310 – Deep Learning for Image Analysis
- IN4160 – Digital system design
- IN4140 – Introduction to Robotics
- IN4050 – Introduction to Artificial Intelligence and Machine Learning
- TEK5600 – Visualization of Scientific Data
- MNKOM4000 – Formidling og vitenskapsjournalistikk
- MCT4052 – Music and Machine Learning
- MCT4053 – Motion Capture