Useful Resources
Last Updated December 2025

A curated collection of books, papers, tools, courses, and recorded talks spanning quantitative finance, programming, finance, and business strategy. By no means is this list exhaustive, nor am I an expert, however if one deeply looks across all of these topics one will become much more informed about a given subject.

Most importantly issues that you encounter during education were most likely experienced previously in one form or another -- ask questions and be willing to be curious and ask silly questions. Understand why things work and one will learn.

Resources Index

Coding

This section introduces the fundamentals to programing, as well as various pointers to languages. Ultimately, this serves as a guide, actually coding up projects will help develop skills and encounter real problems.

Fundamentals

If one was to learn how to code, I would start here as it teaches you discrete thinking, fundamentals, best practices, and problem solving.

Just Starting Out:
- Core Concepts:
  - Harvard University, EdX, CS50 - Introduction to Computer Science (Python, C, SQL, JavaScript, CSS, HTML)
    Argubly the cheapest and most formal broad introduction to programming, abstraction, memory, algorithms, and systems thinking.
  - MIT, OpenCourseWare - Introduction to Algorithms (Python)
    A bit more formal and rigorous learnings of algorithms, recommended prerequisites: (1) Mathematics for Computer Science and (2) Introduction to Computer Science & Programming in Python
  - Princeton, Coursera - Algorithms & Data Structures - graph & string processing algorithms (Java)
    Refining knowledge of data structures, algorithmic paradigms, and performance analysis, recommended prerequisite: Algorithms, Part 1 - Elementry Data Structures, Sorting, Searching Algorithms.
- Theory & Reference:
  - Big-O Cheat Sheet
    Big O notation is a mathematical concept used to describe the performance or complexity of an algorithm in terms of time or space as the input size grows. It provides an upper bound on the growth rate of a function, helping to classify algorithms based on their efficiency.
  - University of San Francisco, Data Structure Visualization
    Interactive explainations of trees, graphs, heaps, and hash tables.
Best Practices:
- Code Quality & Design
  - Clean Code (Rober C. Martin), Github Summary with Links to Book & Resources
    Summary of coding best practices so that the code you make isn't just readable to you in the moment you make it.
  - Refactoring Guru
    Design patterns, anti-patterns, and refactoring techniques.
  - The System Design Primer
    Scalable systems, trade-offs, and architectural patterns. Additional resource (semi-free): System Design School
- Documentation & Style
  - Google Style Guides
    Cross-language coding conventions.
  - Semantic Versioning
    Release and compatibility discipline.
Tooling, Workflow, & Environment:
- Vesion Control
  - Git --fast-version-control
    Git fundamentals and advanced workflows, read Pro Git (Scott Chacon & Ben Straub, 2014)
  - GitHub Docs
    Pull requests, issues, CI/CD basics.
- Development Environments
  - VS Code Documentation
    Debugging, extensions, and language servers. VS Code is great with a ton of support, ultimately use the environment that works best for you: Anoconda, JetBrains, and Google Collab is alright as well.
  - Mastering Terminal Commands
    Useful to know as some languages or OS require some knowledge of how to interact with terminal
- Buld, Test, & Deploy
  - Testing Pyramid
    Unit vs integration vs system testing.
  - Docker Documentation
    Containerization concepts (even without deep ops focus).
Problem Solving & Practice:
- Algorithms, Challenges, & Interview Prep
  - LeetCode
    Standardized algorithm and data structure problems
  - HackerRank
    Structured tracks across domains
  - Codeforces
    Competitive programming and algorithmic depth.
  - Exercism
    Idiomatic practice across languages
- Project-Based Learning
  - Build Your Own X
    Implement systems from first principles (databases, compilers, OS components).
  - Project Awesome
    Curated topic-specific resources.
  - Open Source Contributions (GitHub Issues labeled “good first issue”)
    Find unresolved issues on open source projects to assist and resolve issues that are relatively "straight forward", see a curated list: Good First Issue.
Debugging, Performance, & Systems Thinking:
- Debugging
  - Rubber Duck Debugging
    Conceptual debugging discipline.
  - Language-Specific Debugger Docs (GDB, LLDB, browser dev tools)
    Included LLDB as an example.
- Performance & Systems
  - Latency Numbers Every Programmer Should Know
    Systems-level intuition.
  - High Performance Browser Networking
    Practical systems and networking concepts. Book: High Preformance Browser Networking (Ilya Grigorik).
  - Memory Management Guides
    Stack vs heap, garbage collection, ownership models.
Math & Logic:
- Mathematics Primers
  - MIT, OpenCourseWare - Principles of Discrete Applied Mathematics
    This course is an introduction to discrete applied mathematics. Topics include probability, counting, linear programming, number-theoretic algorithms, sorting, data compression, and error-correcting codes.
  - MIT, OpenCourseWare - Linear Algebra
    This is a basic subject on matrix theory and linear algebra. Emphasis is given to topics that will be useful in other disciplines, including systems of equations, vector spaces, determinants, eigenvalues, similarity, and positive definite matrices. Additional supplement: 3Blue1Brown, Linear Algebra.
  - Stanford University - Probability for Computer Scientists
    Probability is the science of uncertainty —and in computer science, uncertainty is everywhere. Whether it’s predicting what movie you’ll watch next, how secure your password is, or how long an algorithm might take to run, probability plays a key role. It helps computers make smart guesses, deal with randomness, and perform better in the real world. Additional supplements: (1) Carnegie Mellon University - Introduction to Probability Computing (Mor Harchol-Balter, 2024) and (2) Probability in Computer Science (Geeks For Geeks).
Ethics, Security, & Professional Practice:
- Security
  - OWSAP Top Ten
    A list that outlines the most critical security risks to web applications, serving as a guideline for developers to improve their coding practices and enhance application security.
- Licensing & Professional Practice
  - Open Source Initiative - OSI Approved Licenses
    Open source licenses are licenses that comply with the Open Source Definition – in brief, they allow software to be freely used, modified, and shared. To be approved by the Open Source Initiative (also known as the OSI) a license must go through the Open Source Initiative’s license review process. Additional supplement: A Dev’s Guide to Open Source Software Licensing, a Crash Course.
- Ethics
  - Geeks for Geeks - Computer Ethics
    Worth mentioning, be responsible.

Python

Simple, readable, and versatile, suitable for various applications like web development, data analysis, and artificial intelligence.

Learning & Practice:
- Python Tutor
  Visual step-through execution for beginners.
- Real Python
  Practical, applied tutorials with strong explanatory depth.
- Automate the Boring Stuff (Al Sweigart)
  Applied scripting and workflow automation.
Useful Libraries & Resources:
Whenever you get the chance read the documentation:
- Numpy
- Pandas
- Matplotlib
- & much more...

C++

C++ is a general-purpose, object-oriented programming language that was designed by Bjarne Stroustrup in 1979 to be an extension of the C language. It has the features of imperative, object-oriented as well as generic programming models. C++ also has some additional facilities to those in C such as classes, inheritance, default function argument, etc. C++ plays quite an integral role in modern times as many contemporary systems such as operating systems, web browsers, databases, etc. have C++ code in at least some part of their codebase. Moreover, C++ is quite useful in performance-critical areas because of its speed.

Learning & Practice:
- Learn C++
  Highly structured, modern C++ tutorial sequence.
- Compiler Explorer (Godbolt)
  Understand compilation, optimization, and assembly output.
- C++ Insights
  Visualizes compiler transformations.
Useful Libraries & Resources:
- CPP Reference
  De facto standard reference aligned with ISO C++ standards. Additionally, read ISO C++ Core Guidelines, Github for best practices for modern C++

Java

Java is a popular programming language because it is easy to learn, platform-independent, and versatile, allowing developers to create a wide range of applications from web to mobile. Its object-oriented nature and strong community support also make it a reliable choice for both beginners and experienced programmers.

Learning & Practice:
- Java Tutorials (Oracle)
  Structured walkthroughs from basics to advanced topics, reading heavy.
- Exercism (Java Track)
  Idiomatic practice with feedback.
- Codecademy (free tier)
  Introductory syntax and object-oriented concepts.
Useful Libraries & Resources:
Whenever you get the chance read the documentation: Oracle Java Documentation & Java SE API Documentation
- Open JDK
  Language development and implementation details.
- Maven Central Repository
  Dependency management reference.

SQL

Programming resources emphasizing analytical workflows, data engineering, and production-quality code.

Learning & Practice:
- Mode SQL Tutorial
  Data analysis–oriented SQL learning.
- SQL Zoo Tutorial
  Interactive, query-first practice.
- SQL Murder Mystery.
  Using what you learn for fund, additionally see LeetCode's Database section.
Useful Libraries & Resources:
Whenever you get the chance read the documentation: . There is a lot to go through as this is a database language but browse at your leisure.
- PostgreSQL
  Additional object-relational database management system (ORDBMS), opensource
- Database Normalization Guide
  Schema design fundamentals.
- SQL Cheat Sheet, Basic to Advanced (Geek for Geeks)

Rust

Rust is favored for its focus on memory safety, performance, and reliability, making it ideal for systems programming and applications that require long-term maintenance. It also provides strong compile-time guarantees that help prevent common programming errors, which enhances overall software security.

Learning & Practice:
- The Rust Programming Language (“The Book”)
  Primary learning resource maintained by the Rust team.
- Rustlings
  Hands-on exercises aligned with “The Book.”
- Exercism (Rust Track)
  Idiomatic problem solving.
- Rust By Example
  Pattern-oriented learning.
Useful Libraries & Resources:
- Rust Reference
  Language grammar and semantics.
- Rust Reference
  Design rationale and evolution.
- Crates.io
  Package ecosystem.

Mathematics

This section highlights various useful resources surrounding mathematics. Math as a skill is tremendously important to be comfortable with at least (mental math and algebra shows up very frequently). The more that one become comfortable with mathematics (or even learn more deeply about it), the more areas that someone can find areas to apply it.

Foundational to Advanced Mathematics

Public, high-quality resources covering foundational mathematics, undergraduate core topics, proof-based reasoning, probability, and advanced theoretical and applied mathematics.

Foundations & K–12

Foundational Material before entering undergraduate mathematics

Core Undergraduate Mathematics

These are some core materials used across most if not all forms of undergraduate mathematics

Proof, Logic, & Discrete Mathematics

Proofs can be difficult for undergraduates, here are some resources.

Probability & Statistics

Probability and statistics are very intertwined and they serve as a stepping stone for most of quantitiative finance

Advanced & Theoretical Mathematics

After learning the basics of undergraduate, one can move into more difficult undergraduate topics and possibly even at graduate levels

Problems & Challenges

There are many methods to apply your knowledge through computational means or through problems

References & Research

Some relevant research and references to stay up to date on.

Quantitative Finance

Public, academically rigorous resources for learning quantitative finance, spanning mathematics, programming, financial theory, and applied quantitative methods.

Mathematical, Computational, and Financial Foundations

Public, academically rigorous resources for learning quantitative finance, spanning mathematics, programming, financial theory, and applied quantitative methods.

Machine Learning in Quant Finance

Research, Papers, and Data

Introductory Video into Quantiative Finance & Computational Finance

Fantastic introduction and general overview into the world of quantitative finance.

Finance

There exists a great amount of public resources that are high quality for learning core-finance, capital markets, and the advisory industry. These resources emphasize technical skill development, industry context, and career preparation.

General Finance Foundations

Core concepts applicable across all finance roles: accounting, valuation, corporate finance, and financial markets.

Investment Banking

M&A, capital raising, valuation, financial modeling, and transaction execution.

Sales & Trading

Market microstructure, asset pricing, derivatives, and trading strategies.

Management Consulting

Strategy, operations, financial analysis, case interviews, and problem structuring.

Restructuring & Distressed Investing

Bankruptcy, capital structure analysis, distressed valuation, and turnaround strategy.

Private Equity & Hedge Funds

Deal underwriting, leveraged buyouts, portfolio management, and investment research.

Venture Capital

Early-stage investing, startup finance, market sizing, business models, product-market fit, and portfolio support.

General Business

Business is a broad field and its important to rely on specialists to guide learning, however here are some core and advanced business concepts, with focus on supply chain management, entrepreneurship, and executive-level branding and strategy. These materials are best used in combination: academic grounding (universities/research), practitioner insight (consulting firms), and applied execution (founder/operator content).

Supply Chain Management

Emphasis on operations, logistics, procurement, resilience, analytics, and global supply networks.

Foundational Concepts & Frameworks
Operations, Analytics, & Resilience

Entrepreneurship & Venture Building

Focus on ideation, validation, fundraising, scaling, and founder decision-making.

Startup Fundamentals
Strategy, Scaling, & Capital

Executive Branding & Corporate Identity

Resources aimed at senior leaders responsible for positioning, reputation, and long-term brand equity.

Corporate & Executive Branding
Leadership Presence & Reputation

General Business Strategy & Management

Cross-cutting resources relevant to executives, consultants, and operators.

Useful Resources Last Updated December 2025