Oh what a shame, I was planning to sign up for ACM next week. Unfortunately, that was a predictable move from O’Reilly. I bet most of the folks signing up for ACM were actually after O’Reilly’s contents.
I think the only cheaper alternative is during Black Friday period where they give a 100 usd discount.
+1 for Cantrill. I got their SAA last year and learned a lot. It's the most comprehensive AWS online course AFAIK. You not only learn stuff for the certification but also learn many 'whys' and there's lots of practice.
The author builds a small relational database from scratch in java. It supports only a few types and not all SQL commands but it's great to get a big picture.
I write mostly about Python and everything related to it. I decided to create a blog because I wanted to improve my writing skills, English is not my first language and writing in English would be an opportunity to improve it, hopefully.
I'm trying to be consistent and I release two articles a month, one every other week.
The first version I used Hugo but I noticed that I was spending a long time tweaking it and not writing a single word. Then I found https://hashnode.com and gave it a go. They are a blogging as a service and it abstracts away most of the things that I was fighting with. The downsides is that it's not fully configurable but that's the price I decided to pay. But for basic stuff like domain name, analytics, newsletter it works out the box.
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Even though Pharo has evolved a lot from the original smalltalk, the main ideas remain the same. And nowadays the most active development is done by the pharo team. They not only build the software but also tons of high quality content.
I recommend starting with the Pharo Mooc. [1] And then deep dive on their books [2].
From there you can read old classic smalltalk books, such as Kent Back's "Smalltalk Best Practices" and Chamond Liu'a
"Smalltalk, Object and Design".
Even if you can't get an internship you can still learn from real world projects from big companies (or solo devs!) by checking their open source projects.
You won't have a mentor but you can still learn something.
What I suggest is to start with projects you are already familiar with. For example, I work with machine learning and python. I've been learning a lot by studying the code from pytorch, fastapi and other libraries used in this field.
Another great way to learn is to implement new features for projects you use. You can start by replicating existing ones. For example, you can find a PR that added a new feature, then try yourself implementing it and use the actual PR as a guide when you get stuck.