Can you let me know a bit more about the SWE-focused ML path? While I'm interested in ML, I'm slightly more interested in the systems that are built around it. In particular, are there resources that can help me get up to speed in designing (distributed and HW-accelerated) ML systems.
The apps that require permission to read your email and ask for it. They generally provide services like
- Act as a desktop mail client
- Backup your SMS messages to Gmail
- Search your email for forgotten registrations and allow you to cancel
Ideally it should be clear from the context that the app requires this permission. But the problems that plague mobile app and browser extension permission systems exist here as well. The stakes may even be higher.
I'd like to second this suggestion. You will find, or have likely already found, that a lot of the writing you do (class assignments, papers, thesis, etc) will focus primarily on the successes and be written in that expert POV. Documenting the journey is useful for your own records and is a great service if made publicly available. It's also an opportunity to reflect not just the technical topic at hand, but on your personal experience with it.
I really think the two-semester approach works well. The first semester covers basics and intuition and tasks students to implement and extend. The second semester formalizes the material and tasks students to analyze and design algorithms to solve various problems. The first can be taught to first-years and the second to second- or third-years depending on when it's standard to take discrete maths.
My worry is maintaining relationships. I'd happily be the guy who only socializes on Saturday, but I worry about the effects of not meeting with my group of friends as often as they meet with each other.