@alex_prompter: Harvard, Andrew Ng, and Karpathy will teach you AI engineering for free. Most people just do it in the wrong order: Alm…

Harvard, Andrew Ng, and Karpathy will teach you AI engineering for free. Most people just do it in the wrong order:

Almost all of it is free, and the order matters as much as the resources.

1. Start with Python. It’s the language the AI field runs on, and Harvard’s CS50P teaches it better than most paid bootcamps.

2. Once the basics click, learn how Python is used in AI. Andrew Ng’s “AI Python for Beginners” is a free four-part course that bridges writing code and building with models.

3. From there, get a feel for how LLMs work under the hood. 3Blue1Brown’s visual explainers make transformers and attention click.

4. When you want to go deeper, build a small model yourself. Andrej Karpathy’s “Zero to Hero” series takes you from one neuron to a working model, line by line.

5. Next, learn how AI agents actually work. Anthropic’s “Building Effective Agents” is the most grounded guide, and its lesson is to use composable patterns, not heavy frameworks.

6. For hands-on practice, take the CrewAI short course. It teaches you to treat agents like a team of people working together.

7. After that, connect your agents to the real world. That’s what MCP does, wiring models to tools, APIs, and databases, and the official docs are the cleanest place to start.

8. Now build real projects. The open-source ai-engineering-hub repo has dozens of working examples across LLMs, RAG, and agents you can adapt into your own work.

9. Finally, read one book instead of ten. Chip Huyen’s “AI Engineering” covers what you need to ship real applications.

The throughline is simple. Frameworks come and go, so don’t build your skills around them. Master the fundamentals once, and everything on top gets easier, and you’ll stay ahead of the people chasing the framework of the week.

Every link from the roadmap, in order.

1. Python, Harvard CS50P https://pll.harvard.edu/course/cs50s-introduction-programming-python…

2. AI Python for Beginners, Andrew Ng https://deeplearning.ai/courses/ai-python-for-beginners…

3. 3Blue1Brown, neural networks series https://youtube.com/playlist?list=PLZZWrBYkx7Otcjr3eCLZDCgfpqnxMY29s…

4. Andrej Karpathy, Zero to Hero https://youtube.com/playlist?list=PLAqhIrjkxbuWI23v9cThsA9GvCAUhRvKZ…

5. Anthropic, Building Effective Agents https://anthropic.com/engineering/building-effective-agents…

6. CrewAI short course https://coursera.org/projects/multi-ai-agent-systems-with-crewai…

7. MCP docs https://modelcontextprotocol.io

8. ai-engineering-hub https://github.com/patchy631/ai-engineering-hub…

9. Chip Huyen, AI Engineering https://oreilly.com/library/view/ai-engineering/9781098166298/…

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