I am currently trying to prep for SWE roles where my focus would be performance / scalability, so this course is extra topical for me. Thank you for sharing.

I am currently trying to prep for SWE roles where my focus would be performance / scalability, so this course is extra topical for me. Thank you for sharing. Here are some other resources for people interested in improving their understanding of performance: - "Computer Architecture: A Quantitative Approach" by Hennessy and Patterson. The "Computer Organization" book by the same authors is also good. Both of these resources were extra useful when building deeper intuitions about GPU performance for ML models at work and in graduate school. - CMU's "Deep Learning Systems" Course is hosted online and has YouTube lectures online. While not generally relevant to software performance, it is especially useful for engineers interested in building strong fundamentals that will serve them well when taking ML models into production environments: https://dlsyscourse.org/ https://dlsyscourse.org/ - Compiler Explorer is a tool that allows you easily input some code in and check how the assembly output maps to the source. I think this is exceptionally useful for beginner/intermediate programmers who are familiar with one compiled high-level language and have not been exposed to reading lots of assembly. It is also great for testing how different compiler flags affect assembly output. Many people used to coding in C and C++ probably know about this, but I still run into people who haven't so I share it whenever performance comes up: https://godbolt.org/ https://godbolt.org/