Photo by João Silas on Unsplash
After joining Google and life catching on a regular pace, I start to assume that I would have the capacity to read more after work.
Last weekend, I borrowed the only CFA curriculum book from the San Mateo Public Library. Unfortunately, the book is on Level II, and I could really use a more entry-level textbook. After browsing through official website of CFA, it turns out that I can get access to the ebooks of CFA Curriculum Level I by registering for the exam itself. When reading is tied to a test, there comes -- more or less -- pressure to read.
You may argue that some pressure is healthy for pushing you to read at an actually productive schedule/pace, but I'm not very sure if that's suitable for my case, where I'm still struggling ramping up with work. In this consideration, I may as well pick up a tutorial book on Go lang, or TypeScript.
Speaking of work-related books: At my new office desk lies an unclaimed copy of Design Patterns. I asked around, and no one seemed to know its owner. I guess it's mine now.
- Software Project Survival Guide, and
Both of the books are much easier to read than the Design Patterns, mostly because 1) they did not involve an old programming language that I don't know of, and 2) the use of first-person narrative made references much much clearer. Thanks to the ease, I finished the two by the beginning of December, feeling more confident about knowing what's going on at work.
Now that I have finished a couple of work-related books, it might be time to pick up one unrelated to software development. Because I had returned the CFA Curriculum book before it's due (which I didn't found readable anyways), this was also a chance to explore another subject.
Around the end of 2019, I picked up Psychology (11th Ed), by David G. Myers and C. Nathan DeWall. Yes, it's a 900-page textbook, not a easy read like any of the 50+ lightnovels I devoured; but here's the beauty of textbooks: If you read them back-to-back without academic pressure (exams, etc.), it is one of the best ways to get a comprehensive and systematic view into a subject.
The last textbook I've read this way was Introduction to Computational Materials Science, during the summer right after my graduation from college and before my entering to the Scientific Computing master's program. I have to confess that I barely remember any detail from this book, but had I stayed in the program (rather than transferring to Data Science within 3 weeks of joining UPenn), the book-reading experience would surely be more valuable.