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title: How I&#x27;d Become an AI Engineer in 2026 (Even with No CS...
description: A senior applied scientist at Twitch, self-taught with a non-CS background, lays out a roadmap for becoming an AI engineer from scratch. The plan covers seven...
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# How I'd Become an AI Engineer in 2026 (Even with No CS Degree)

**[YouTube](https://daily.dev/sources/youtube)** · 16 min read · 2 upvotes · 0 comments

## Summary

A senior applied scientist at Twitch, self-taught with a non-CS background, lays out a roadmap for becoming an AI engineer from scratch. The plan covers seven skill buckets (programming, math, ML fundamentals, AI engineering basics like LLMs/prompting/RAG, agents/MCP, production infrastructure, and interview prep), recommends free/cheap learning resources (Scrimba, 3Blue1Brown, Google's ML crash course, DeepLearning.AI, Hugging Face, Chip Huyen's 'AI Engineering' book), and advises building a small personal project before scaling it to production. It also covers networking strategies for candidates without traditional degrees, and closes with a plug for the creator's paid 8-week cohort and Supabase's sponsored agent skills feature.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.youtube.com/watch?v=8c8Rrhd2oxo>

## Questions this post answers

### What is the difference between an AI engineer and a machine learning engineer?

An AI engineer builds applications on top of pre-trained models like Claude, GPT, or Gemini, creating systems that summarize information or automate tasks. A machine learning engineer instead uses data to train custom models from scratch, such as a recommendation system or fraud detection model. Neither role invents new model architectures, which is the work of AI researchers.

_daily.dev helps developers weighing AI engineer versus ML engineer paths track the distinction as roles evolve._

### What skills do I need to become an AI engineer with no CS degree?

Seven skill areas matter: Python and software engineering fundamentals, applied math intuition (linear algebra, probability, statistics, calculus), machine learning fundamentals, core AI engineering skills (LLMs, prompt engineering, context engineering, RAG, evaluation), AI agents and MCP, production infrastructure (APIs, Docker, CI/CD, monitoring), and interview prep including coding and system design.

_Track which of these AI engineering skills to prioritize next using daily.dev as you build toward a job._

### Why does Supabase recommend using agent skills when coding with AI assistants?

Supabase changes its CLI commands, security requirements, and best practices frequently, so a coding agent's training data can be outdated. Agent skills are markdown instruction sets that tell agents like Claude Code, Cursor, or others to check live Supabase docs before writing code rather than relying on stale training data, and they can be installed with a single command.

_Developers relying on coding agents for Supabase projects can follow tooling updates like this on daily.dev._

## Similar posts on daily.dev

- [How to Become an AI Engineer Fast \(Skills, Projects, Salary\)](https://daily.dev/posts/how-to-become-an-ai-engineer-fast-skills-projects-salary--t2mwlzyhz) · Towards Data Science · 9 upvotes · 0 comments

---

Tags: [#career](https://daily.dev/tags/career), [#llm](https://daily.dev/tags/llm), [#rag](https://daily.dev/tags/rag), [#supabase](https://daily.dev/tags/supabase), [#ai-engineering](https://daily.dev/tags/ai-engineering)

[View this post on daily.dev](https://daily.dev/posts/how-i-d-become-an-ai-engineer-in-2026-even-with-no-cs-degree--tf9gstkdt)

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