moh4696/10-ai-careers-roadmap — explained in plain English
Analysis updated 2026-05-18
Pick one of ten AI career paths and follow its curated free roadmap.
Find free courses, videos, books, and practice exercises for a specific AI-related job.
Use the recommended starting point on each career page to build a study plan.
| moh4696/10-ai-careers-roadmap | 0petru/sentimo | 0xblackash/cve-2026-46333 | |
|---|---|---|---|
| Stars | 17 | 17 | 17 |
| Language | — | Python | C |
| Setup difficulty | easy | moderate | moderate |
| Complexity | 1/5 | 3/5 | 4/5 |
| Audience | general | developer | researcher |
Figures from each repo's GitHub metadata at analysis time.
10 AI Careers Roadmap is a free library of learning resources built to accompany an article on X (formerly Twitter) titled "10 AI Careers Quietly Paying $135K to $1M+ in 2026." The repository does not contain a course or software of its own. Instead, it organizes links to free courses, videos, books, and hands-on practice into ten separate roadmap pages, one for each career path covered in the article. The ten careers include AI Engineer, Machine Learning Engineer, Robotics Engineer, LLMOps Engineer, AI Consultant, Cybersecurity Engineer, Cloud Engineer, AI Product Manager, Data Engineer, and AI Research Scientist. Each career has its own markdown file inside a careers folder, and each file starts with a short recommended starting point rather than a long unsorted list of links. The README suggests picking one career path at a time instead of trying to learn all ten at once, working through the recommended starting point first, then branching out to more resources once the basics are in place. It also encourages building small public projects on GitHub as proof of skill, and joining the communities linked on each page. A small set of emoji labels mark each resource type: free, free to audit with an optional paid certificate, video, course, code or repo, book or documentation, and hands on practice. This lets a reader scan a page quickly and see at a glance what kind of resource they are looking at and whether it costs anything. The project accepts contributions of additional free resources through a CONTRIBUTING file, with the stated condition that anything added stay free and friendly to beginners. It is released under the CC0-1.0 license, meaning it is placed in the public domain and can be copied, forked, shared, or reused with no attribution required.
A free, curated collection of learning resources and roadmaps for ten AI-related careers, meant to accompany an X article on high-paying AI jobs.
Public domain: copy, share, or reuse it however you like, with no attribution required.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly general.
This repo across BitVibe Labs
double-check against the repo, no cap.