curious16

Learn to Program: Crafting Quality Code

https://www.coursera.org/learn/program-code

If you really care about learning, carve out time from your daily routine and progress little by little in chunks.

Wow! I didn't know that Shriram's introductory course had lecture videos available. I will take a look at them.

Btw, I also liked Hubbard and Hubbard.

Another book I liked was Computer Systems: A Programmer's Perspective at https://csapp.cs.cmu.edu/

Check out Fast.ai's two part course.

What language do you work in now? If it is an imperative language do you avoid state as much as possible?

And how does one learn reasoning skills?

"My gut feeling says that students never learned strong reasoning skills and mathematical induction."

This quote from the linked article resonates with me quite a lot. I see people trying to understand recursion in code and not getting the hang of it.

CMU is one university where it's CS curriculum teaches functional programming after a rigorous course on Pure Mathematics Intro - https://www.math.cmu.edu/~jmackey/151_128/welcome.html. The functional programming course (15-150) materials are not public, but they use SML and uses heavy use of induction proofs and recursive implementations.

The other line of programming pedagogy argues that only simple high school algebra is enough to teach programming via recursion. I am talking about How to Design Programs: https://htdp.org/ and now the DCIC book: https://dcic-world.org/. They argue that looking at the data and its inherent structure is enough.

The above two approaches are mostly polar opposites of each other. I want to know what other HNers think about this.

Not a book. But a course by Prof Keith Devlin on Coursera called Introduction to Mathematical Thinking.

There is a 3 part course on Coursera by U of Washington Prof Dan Grossman called

Programming Languages A: https://in.coursera.org/learn/programming-languages

Programming Languages B: https://www.coursera.org/learn/programming-languages-part-b

Programming Languages C: https://in.coursera.org/learn/programming-languages-part-c

It will surely make you a great programmer if you haven't dabbled with functional languages before. Even if you have, it still makes a great course only for the teaching style of Dan.

Programming -

Stick to a specific set of tools YOU are comfortable with. Don't go with the newest fad. What matters are your skills and concepts. Not what tool you use. A skilled craftsman can use very basic tools to build impeccable creations while a naive one with the latest fancy tools can create junk. So don't jump editors, just learn the one you are comfortable with and do is in much depth.

Math -

Don't look for the golden trick. Just solve more and more problems and you will eventually get good at recognizing patterns.

Calling Bullshit: https://www.callingbullshit.org/videos.html

To quote from the syllabus of the course:

" Our learning objectives are straightforward. After taking the course, you should be able to:

- Remain vigilant for bullshit contaminating your information diet.

- Recognize said bullshit whenever and wherever you encounter it.

- Figure out for yourself precisely why a particular bit of bullshit is bullshit.

- Provide a statistician or fellow scientist with a technical explanation of why a claim is bullshit.

- Provide your crystals-and-homeopathy aunt or casually racist uncle with an accessible and persuasive explanation of why a claim is bullshit.

We will be astonished if these skills do not turn out to be among the most useful and most broadly applicable of those that you acquire during the course of your college education."

Any specific books you have in mind?

Why not? Of course!!

Any particular set of courses you have in mind?

I believe you are talking about this book.

Dive into Deep Learning: https://d2l.ai/

No. But the way Calculus is taught in the US university freshmen, this book looks like a rigorous introduction to Analysis, even though it is not. It is just a sensible introduction to single variable calculus without hand wavy arguments.

> Methods of Mathematics Applied to Calculus, Probability, and Statistics is one of a kind.

I have tried finding this. Couldn't even find on libgen.

If you have extensive experience in programming you may try out SICP if you find HtDP too slow.

What is the prerequisite to read this book?

Any specific books or resources you have in mind?

You are a calisthenics enthusiast? How long have you been training? What is your routine?

What other CS books did you find amusing?

How does it compare to the 1st edition?

I have heard about the book and the courses. What do you come out with after completing either of them? Can you read research papers and implement them and try to beat state of the art?

I am talking about a mixture of both such that both the applied and theoretical parts are well explained. But not in a theory first way.

More like this:

Here is a tool you can use to perform these many tasks in these many situations. Now that you have seen how it works, let us investigate why it works and where does it come from (maybe with a bit of history). Because stories are always easier to remember.

Added to the post details.

Can you share more about your venture?

Enough income so that you don't have to do a traditional job at a company as an employee.

I am going to list two books.

Fiction: Jurassic Park by M Crichton. Just for the world build up and writing

Non-Fiction: The Machinery of Life by David Goodsell. I fell in love with biology again after reading this book. The wonderful illustrations make the book come alive.

> Deep Learning for Coders by Jeremy Howard

Can you discuss a bit more on this choice?