Rust_RL VS hll-rust

Nothing wrong with that! I also learned Rust while writing DL/RL algorithms: https://github.com/ZuseZ4/Rust_RL/

Nice, also worked on tic-tac-toe / Neural Networks / Agents to get into Rust / RL: https://github.com/ZuseZ4/Rust_RL/

I'm just finishing undergrad studies and wrote a Reinforcement Learning Library (https://github.com/ZuseZ4/Rust_RL) including double-deep-q learning with replay buffer in pure rust to learn the language. I'm also trying to get Rust into shape for data science, but I'd vote against using it as an example in introduction classes. Pure Python (which wraps around C++) will usually be simpler and faster for users, leaving few reasons to focus on this in a lecture. Furthermore, even if we are into ML, there are probably quite a few people who'd pick such a lesson to learn about Rust, not about Machine Learning. For the latter, there are at least in the Universities I know, more than enough offers.

I like your outline. I think your students will have a lot of fun and learn a lot! In 2018/19, I also attended a rust lecture at my university. You can find its outline and slides here. As a final project, we could choose between different topics, like actor model, P2P network, distributed key-value database or Software Distributed Shared Memory (SDSM). Some fellow students and I, for example, implemented "Chord" (a protocol and algorithm for a peer-to-peer distributed hash table), which was a great experience. Our repo can be found here https://github.com/ndrsllwngr/hll-rust