---
type: entity
subtype: person
title: "Andrew Ng"
description: "AI educator behind the Coursera 'AI for Everyone' course and the machine learning, deep learning, and NLP specializations Cole recommends for AI fundamentals."
tags: [ai-education, fundamentals, learning-roadmap]
videos: [the-only-ai-developer-roadmap-you-need-in-2024]
created: 2026-07-21
updated: 2026-07-21
---

# Andrew Ng

Andrew Ng is the AI educator whose courses Cole hands people as the on-ramp to AI engineering. He shows up exactly once in this catalog, but at a load-bearing spot: step two of the [AI Agent Learning Roadmap](../../concepts/ai-agent-learning-roadmap.md), where you learn how AI models and LLMs are actually trained and where they fail. Cole's recommendation is direct: "there's also a six-hour course corsera AI for Everyone by angre NG that I've done I'd highly recommend this one" ([0:03:09], transcript spelling). Ng's machine learning, deep learning, and NLP specializations sit one tier further out, in the roadmap's explicitly optional branch, because GPT and Claude are strong enough that most builders never need to train a custom model.

What makes Ng useful in Cole's framing is the *dosage*. The roadmap treats fundamentals as something you move through fast, not something you camp in: a six-hour course is the right size, six months of theory is not. That posture is the whole reason Ng appears here as an entity rather than a footnote. He represents the legitimate, compressed version of "learn the fundamentals," standing against both the skip-everything approach and the guru framing Cole attacks in the same video, where [Prompt Engineering](../../concepts/prompt-engineering.md) gets sold as a $300k career instead of a few hours of study.

Everything downstream of Ng in that roadmap is hands-on: building directly against the OpenAI and Anthropic SDKs, then [Retrieval-Augmented Generation (RAG)](../../concepts/rag.md), then agents. Ng gets you literate; the build steps get you employable.

## Part of

- [AI Agent Learning Roadmap](../../concepts/ai-agent-learning-roadmap.md) - Cole's ordered path for learning to build AI agents, from Python and LLM fundamentals through no-code prototyping, coded agents, RAG, and multi-agent architectures.

## Contrasts with

- [Learn by Building](../../concepts/learn-by-building.md) - Learning AI engineering by building real projects, forking open source, and rebuilding from docs rather than passive study. Ng's courses are the fast literacy pass you take *before* this, not a substitute for it.

## Related

- [Prompt Engineering](../../concepts/prompt-engineering.md) - The craft of wording, structuring, and constraining a prompt so an LLM reliably produces the answer you want.
- [Retrieval-Augmented Generation (RAG)](../../concepts/rag.md) - Grounding an LLM's answers by retrieving relevant documents from an external knowledge base and injecting them into the prompt at query time.
- [What Is an AI Agent](../../concepts/what-is-an-ai-agent.md) - An AI agent is a large language model given tools to interact with the outside world and take actions.
- [Fine-Tuning](../../concepts/fine-tuning.md) - Adapting a base model to a task or domain via additional training, weighed against just prompting a stronger general model.
- [Scrimba](../organizations/scrimba.md) - Interactive coding-education platform where tutorials become pair-programming sessions you can edit in real time.
- [Cole Medin](./cole-medin.md) - AI engineer and educator whose YouTube channel and Dynamous community teach agentic coding; creator of Archon and the source of this entire knowledge base.

## Sources

- [The ONLY AI Developer Roadmap You Need in 2024](../../sources/the-only-ai-developer-roadmap-you-need-in-2024.md) - "[0:03:09] there's also a six-hour course corsera AI for Everyone by angre NG that I've done I'd highly recommend this one."
