debanjan16

>To me, functional programming was tremendeously useful when learning to program.

Did you use any specific book for the purpose?

An online book by Michael Nielsen : http://neuralnetworksanddeeplearning.com/

It starts from basics and builds a CNN to recognize handwritten digits. I found it very helpful during my start of the journey.

> My intro class was taught in lisp

Was it SICP in Berkeley?

I would echo OP's suggestion of learning approximation problems for getting better at math.

There is a course on MIT OCW by Prof Sanjoy Mahajan called Street Fighting Mathematics: https://ocw.mit.edu/courses/18-098-street-fighting-mathemati....

It uses a book of the same name. You can find more about it here: http://streetfightingmath.com/index.html

There is also Concrete Mathematics by Don Knuth et al. You can find it for free as a pdf if you google properly. It is a mixture of discrete and continuous math.

Also Polya's How to Solve It.

+1

I have a few in mind:

1. Journey into Mathematics by Rotman

2. Street Fighting Mathematics by Sanjoy Mahajan

For Programming:

1. How to Code: Simple Data & How to Code: Complex Data by Gregor Kiczales (edX)

They teach you how to use a systematic design recipe to solve poorly formed problems using code and doesn't need anything other than school algebra

2. Programming Languages A, B & C by Dan Grossman (Coursera)

Made different paradigms click finally to me

This is an ongoing serious by Andrej Karpathy called Neural Networks from Zero to Hero: https://www.youtube.com/playlist?list=PLAqhIrjkxbuWI23v9cThs...

Can you expand a bit more?

Knowledge should be open to all. Thank the people who made such resources publicly available to all.

Ah! This question which offends as many people as it pleases (because it is a correct question).

Some people in academia are actually trying to solve this issue. You may look at:

1. How to Design Programs : https://htdp.org/

2. Data-Centric Introduction to Computing: https://dcic-world.org/

3. A course based on the above book: https://learnaifromscratch.github.io/software.html

You can view the lectures here: https://www.youtube.com/playlist?list=PLE18841CABEA24090

Both the book and the lectures are important!

1. Structure and Interpretation of Computer Programs by Abelson and Sussman

2. Computer Systems: A programmer's Perspective

Learning Linear Algebra has helped me a lot in scientific computing.

Build strong back muscles and core muscles. Do rowing movements like inverted bodyweight rows or maybe pullups if you can.

I would love to know more about your process/journey of self studying mathematics and the books that helped.

I still believe with proper discipline, the go to book for learning how to program should be How to Design Programs at https://htdp.org/

There are two courses by UBC's Gregor Kiczales based on this book on edX. You can do both simultaneously.

Yes, definitely teaching how to solve a problem should be included.

Which Algorithms course?

Yes, even for their intro course 15-122 the course notes are excellent.

>What I found is that there's much better content overall one tier down

Which school's content are you talking about?

CMU courses doesn't have videos, atleast for most of the core courses. Was that a hurdle to your learning?

What courses did you use from CMU and which major?

For me it was How to Design Programs (HtDP) by Felleisen et al.

Before that I wrote code that I know hate from my core. It really taught me how to write code properly using functions. More than that it taught me how to break down a problem into parts and solve each part correctly.

Very few books teach problem solving and programming together is such a fantastic way.

Do you have any book recommendations?

It is not a MOOC, but two books with overlapping authors.

1. How to Design Programs: https://htdp.org/

2. A Data-Centric Introduction to Computing: https://dcic-world.org/

I am not sure about the language agnostic part. But I have an unusual book in mind which is out of print. It is by Udi Manber. The name is Introduction to Algorithms: A Creative Approach.

The book emphasises on the "design" part of the process. It shows how to employ induction to design algorithms. It is unlike any other book I have ever seen in this domain.

You can find it here: https://doc.lagout.org/science/0_Computer%20Science/2_Algori...

I don't know about MOOCs much. But there is a book called How to Design Programs. You can read that. And it is available for free at https://htdp.org/

I can wholeheartedly recommend two books:

1. How to Design Programs : https://htdp.org/

2. A Data-Centric Introduction to Computing : https://dcic-world.org/

Sure, ecosystems are most useful. But they are based on the languages core features.