From-0-to-Research-Scientist-resources-guide

Why we included this project

This guide collects and orders the material you would need to go from a programming or CS background toward a research scientist role with a deep learning and NLP focus. Instead of just dumping links, it sequences the math foundations first (linear algebra, probability, calculus, and optimization) and then moves through machine learning, deep learning, reinforcement learning, and natural language processing. Each resource carries a difficulty rating and a relevance bar showing how strongly it applies to deep learning versus machine learning or computer vision, which helps you decide where to start. The author also lays out two routes: bottom-up for people who want theory before applications, and top-down for hands-on learners. If you are planning a multi-month self-study, this works as a practical syllabus rather than a deployable tool.