02461 Introduction to intelligent systems
Rapporteur: Mikkel Schmidt
Exam: Written examination and reports
Written exam (weight 40%) and individualized group report (weight 60%)
Participation in project work activities are mandatory.
Exam duration: 2 hours
Aid: One handwritten page (provided or own notes?)
Evaluation: 7 step scale, external examiner
General course objectives
To give the participants a basic knowledge of
- defining aspects of intelligent systems,
- applications of intelligent systems in image, audio, text and game data,
- computational tools for artificial intelligence, and
- engineering applications of intelligent systems.
Learning objectives
- Describe key components of intelligent systems: Sensing and active data collection, machine learning, statistical evaluation and communication
- Discuss the role of AI tools in application domains such as bio-medicine, business and commerce, information retrieval and social media
- Discuss safety and ethical challenges in AI. Biases and stereotypes, privacy and societal impact.
- Apply real-time AI tools to data such as image, audio, text and games. Discuss performance obtained in individual and classroom experiments
- Use techniques for evaluation of performance and basic debugging of AI.
- Apply scientific Python programming tools including Jupyter notebooks, Numpy, and Pytorch
- Apply tools for managing of files and programs in the terminal
- Apply tools for managing programming projects including version control
- Evaluate and provide feedback for the work of other students
Content
The course provides a general introduction to AI and its tools. The course is based on a set of AI tools with applications in image, audio, text and games. A first motivating introduction to signals, machine learning, visualization and computational tools necessary for engineering AI systems. Discussion of ethics, privacy and societal impact.
Course literature
Course notes
Remarks
**** workshop notes ****
Written exam part
Change written exam to written aids
Aids allowed: One hand written page (not currently an option at DTU)
Make it a course acitvity to make the notes and do mock exams
Project work
All AI aids are allowed, and it works okay.
Checkpoints during the period - mandatory to show up x number of times for feedback.
Require hand in code also - as part of the assignment/report.
More strict report format? Word counts for each section + number of figures/tables?
Texcount on Overleaf?
Exam platform
DTU must provide some service
- Controlled digital platform
- Scanning service
Other ideas
Can we change the course to not be graded.
Make a report where each section is just the prompt
Make a written exam (no aids) after handing in a report, asking to summarize. Integrate prompting into teaching?
Could they compare own solution with AI solutions?