• C++ Programming for Financial Engineering
    Highly recommended by thousands of MFE students. Covers essential C++ topics with applications to financial engineering. Learn more Join!
    Python for Finance with Intro to Data Science
    Gain practical understanding of Python to read, understand, and write professional Python code for your first day on the job. Learn more Join!
    An Intuition-Based Options Primer for FE
    Ideal for entry level positions interviews and graduate studies, specializing in options trading arbitrage and options valuation models. Learn more Join!

Self-learning and implementing numerical methods - VS 2019

Hi friends,

I have been self-learning numerical methods and ODEs for a while. I figure, the best way to learn numerical methods is to build solvers, write naive implementations of matrix methods (of course these are grossly inefficient) and study their myriad applications.

I've wanted to write theory, comments and remarks alongside C++ code. I am using the LaTeX extension for Visual Studio. While not a robust solution, it makes my life easy, it's a crude version of Jupyter's notebook. Here's how it looks :


Do you guys like it? If you think, there are better methods to do something like this, I'd love to hear.

Taking notes in LaTeX, copying and pasting code snippets was becoming more laborious, especially since I also have to take exams on these areas, and I have limited time. Theory interspersed with code and implementation is just what you'd need, when you're learning by doing.