AI Engineering for Beginners: For Coders and Non-Coders

About this course

“This course contains the use of artificial intelligence.”

AI Engineering for Beginners: Build 8 Real LLM Applications

This isn't a theory course. This is hands-on AI engineering where you build 8 complete LLM applications from scratch—the kind you can ship, use, or show employers.

Most AI courses pick a lane: either they're closed-model tutorials (ChatGPT prompts) or they're deep in open-source weeds. This course covers the full spectrum. You'll work with OpenAI, Anthropic, Deepseek, Ollama, Hugging Face, and understand when to use each. You'll learn prompt engineering, API integration, RAG systems, fine-tuning basics, and how to actually think like an AI engineer—not just follow steps.

What You'll Build:

Eight projects that teach real engineering principles. Each one targets a different use case and tech stack combination. You'll handle model selection, building retrieval systems, working with vector databases, integrating external APIs, and handling edge cases. By the end, you won't just know how LLMs work—you'll know how to architect applications around them.

Who This Is For:

Both technical and non-technical people. If you're a developer, you'll learn AI-specific patterns and architecture. If you're non-technical, I walk you through everything. No prerequisite coding required, but if you have it, you'll move faster. Either way, you'll understand the engineering decisions behind production AI applications.

What You'll Know:

• How to choose between open and closed models for different problems
• Prompt engineering that actually works in production
• Building RAG systems for knowledge-grounded AIFine-tuning basics and when it mattersAPI integration and handling costs at scale
• Deploying applications people can actually use

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