Overall grade

The grade for the course is computed as follows:

• 25% Process (quality of the progress reports)
• 25% Final project presentation (clarity and structure of the presentation, quality of the slides, engagement with the audience)
• 50% Final project report (quality of the final reports and results)

Grading of the assignments

The assignment contains 8 steps. Each step corresponds to a lecture. We strongly recommend to work on the steps of the assignment as the course progresses. To encourage this, 25% of the grade is given to the process (see above). If you work consistently - implement the code and work on the report, by the end of the course you will have finished the assignment and will only need to prepare the presentation.

Each step of the assignment will be evaluated on base of 10. Note that there are some bonus questions, implementing which will give you an advantage in case you fail to implement other questions.

When grading the assignments (both the progress reports and the final reports) we are evaluating the quality of the writing (conciseness, logical flow, structure), the quality of the experiments (thoroughness, the story the experiments tell, presentation of the results) and implementation (whether implementation does what it intends to do). For more details on how to structure assignments and report the experiments consult the Technical tips.

Group formation

We encourage you to work on the assignment in groups of two. In case you have a strong preference to work in a group of three, or alone, this is also possible. If you do not know how to find a group-mate to work with, use the Students channel for this.

Code plagiarism and usage of libraries

You are not allowed to use code available in internet. We will check the code for plagiarism and the copied code will not count as an accomplished task. You are also not allowed to copy the code from each other. As an exception to the above statements: You can use graph-theoretic libraries (for calculating DFS, BFS, shortest paths) and libraries for statistics, numerical methods, data analysis, and graphics. However, we strongly encourage you to implement as many of the algorithms involved in the assignment yourselves. You are not allowed to use graph visualization libraries.