Exam: Written examination and reports
Written exam (weight 40%) and individualized group report (weight 60%)
Participation in project work activities are mandatory.
Exam duration: Written exam: 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
A student who has met the objectives of the course will be able to:
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 activity 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?