Homeworks

[tm-pham]

• Figure out 5 home works for the course (we can maybe choose from projects)
• Gillespie algorithm or a MCMC sampler (Mui)
• Optimization algorithm (George)

[gvegayon]

We can find an algorithm to be implemented using R (for instance) and run it using parallel computing (we don't have a homework with that).

Another homework could also be related to implementing another algorithm in R (or C++, if they wish). It could be something like an optimization algorithm (Newton-Raphson, for instance) without using the optim function.

The last one could be about using Slurm for some simulation or data analysis.

[gvegayon]

Part of the assignment could be something like the following:

1. Implement the algorithm as best as you can (no AI allowed).
2. Ask an AI to solve the problem for you, and see how it goes (ensure to share the prompt you use, as well as the model).
3. Reflect about the differences between your code and the AI's implementation. What did you learn, what would you have done differently to get a better result from the AI. (and don't use AI to write this part).

Something like this...