Note: click on the following link, and actually read it; it's part of the syllabus:
Introduces evolutionary algorithms, a class of stochastic, population-based algorithms inspired by natural evolution theory (e.g., genetic algorithms), capable of solving complex problems for which other techniques fail. Students will implement course concepts, tackling science, engineering, and/or business problems.
- Grade of "C" or better in both:
- Comp Sci 2500
- >3000-level Probability and Statistics course
- A good attitude, work ethic, and an interest in EC!
This class is more flexible in regard to which OS, with some notes for you to consider:
- I develop assignments on Fedora, and the Docker containers we grade on git-classes CI/CD will be Fedora.
- OpenSuse is easy, rolling, pleasant, well-documented. I have a convenient OVA for newbies, and non-CS students in courses like Bioinformatics (see syllabus). It should generally work as Fedora would in the relevant ways for assignments (and not break things for you).
- Debian-based would be OK, though you'll have more work for setup, as it's antiquated. It also comes out of the box with stuff like the PATH set up incorrectly...
- If you run some other Linux else bare-metal, it'll almost certainly work, and I'm happy to field questions.
Python, C, Java (really!), Clojure (Lisp on Java), and/or push (pyshgp)