# ahmedbahaaeldin/From-0-to-Research-Scientist-resources-guide

Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.

Repository: https://github.com/ahmedbahaaeldin/From-0-to-Research-Scientist-resources-guide
Canonical: https://ross.abutalabs.com/products/from-0-to-research-scientist-resources-guide
License Family: other
Topics: machine-learning, deep-learning, linear-algebra, probability, calculus, books, lectures
Last push: 2024-03-14T10:57:31+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 1996, "days_push": 902, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 7674, forks 1065 (observed 2026-08-28T04:10:02.341825+00:00)

## What it is
A curated learning guide that maps a path from basic programming knowledge to AI research scientist, covering math foundations, machine learning, deep learning, reinforcement learning, and NLP. It organizes books, lectures, and courses with difficulty and relevance ratings, supporting both bottom-up and top-down study approaches.

## Use cases
- learn machine learning from scratch
- find the best linear algebra resources for deep learning
- build a study plan to become an AI research scientist
- curated list of deep learning and NLP books and lectures
- learn the math foundations needed for AI
- self-study roadmap for artificial intelligence

## When to choose
- you want a structured, opinionated roadmap with rated resources for AI and NLP
- you need math foundations (linear algebra, probability, calculus) before ML
- you are a self-learner or undergraduate wanting free books and lectures

## When to avoid
- you need hands-on code, tutorials, or runnable projects rather than resource links
- you want a formal course with certificates or instructor support
- you need up-to-date coverage of the newest LLM-era research

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation
- domain: machine-learning, deep-learning, tutorials, mathematics, artificial-intelligence
- platform: cross-platform
- tags: curated-resources, study-guide, math-foundations, research-scientist, books-and-lectures, natural-language-processing

## Member repositories
- ahmedbahaaeldin/From-0-to-Research-Scientist-resources-guide (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:02.341825+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:36:03.043005+00:00, confidence not recorded.
  - readme: https://github.com/ahmedbahaaeldin/From-0-to-Research-Scientist-resources-guide (fetched 2026-08-28T04:10:02.341825+00:00, sha df00216c8377)
- Data as of 2026-08-30T08:39:29.467469+00:00.