Coursework
This page gives an overview of the work you will do during the course.
Theory assignments
The theory assignments help you develop your understanding of the central concepts, models and algorithms presented in the course.
Diagnostic quizzes
The diagnostic quizzes are short, multiple-choice online tests that help you check your understanding of the video lectures. We will also use these quizzes to identify concepts that many students find difficult and discuss them in more detail during class.
If you complete all quizzes from a given unit on time, you earn a “wildcard”. This will automatically turn one wrong answer from that unit into a correct one on the final test.
In-class assignments
The in-class assignments let you explore the course content in more depth together with your coursemates. You complete these assignments in small groups. To get credit, you must attend the teaching session when the assignment is given. There is one in-class assignment per unit.
Final test
In the final week of the course, you will take a supervised test consisting of questions sampled from the diagnostic quizzes. The test has 40 questions in total, 10 from each unit.
Grading criteria
The theory assignments are graded as Pass or Fail. To pass, you must complete at least three in-class assignments and score at least 36 points on the final test (including wildcards).
If you miss one of the in-class assignments, you may complete a replacement assignment. You can submit this either during the course or during one of the reexam periods. You can also retake the final test in a reexam period.
Laboratory assignments
The laboratory assignments or “labs” train you in implementing and evaluating the models and algorithms presented in the course. Each lab asks you to explain, modify or write code and to run and analyse experiments. You work on these assignments individually or in pairs. There is one lab for each unit.
Lab portfolio
At the start of the course, you will create a Git repository to serve as your virtual portfolio for your work on the lab assignments. You will then use the portfolio throughout the course to collect:
- The drafts and final versions of the labs you work on.
- The feedback you receive from the teachers.
- Your notes on how you used that feedback to improve your work.
- Your notes on how you used AI tools in your work.
If you need help with the labs or want feedback on your work, get in touch with the teachers via email or Teams or book an appointment. You can also get a written review of each lab. For this, you must upload the lab in question to Lisam before the specified deadline.
Oral exam
In the final week of the course, you will take a 15-minute oral exam based on your portfolio. During the exam, you will present two tasks from the labs:
- One from a list of tasks you propose when you register for the exam.
- One task chosen by the examiner.
For each task, start with a brief explanation of the context and background, then explain your solution as you developed it during the lab. Highlight how you worked with the feedback from your teachers, and how you used AI tools. Keep your presentation to 5 minutes per task.
Grading criteria
The laboratory assignments are graded as Pass or Fail. To pass, you must produce a portfolio and pass the oral exam. Your portfolio should:
Include completed versions of all labs. You should have worked on each task and be prepared to explain your process and results during the oral exam.
Clearly show how you incorporated feedback into your work. Include the written review and any oral feedback provided by your teachers for each lab, along with notes on how you applied that feedback.
Include notes on how you used AI tools in your work.
Demonstrate a professional level of effort. This means using academic language, appropriate terminology and ensuring your writing is clear and free of grammar mistakes.
If you are unable to produce a complete portfolio during the course, you can submit it during one of the reexam periods. You can also retake the oral exam in a reexam period.