Best AI Development & Engineering Courses

AI Development & Engineering Courses — Frequently Asked Questions

What programming languages do these courses use?▾

Python is the primary language across AI development courses, given its dominance in the ML ecosystem. Some courses also cover JavaScript/TypeScript for building AI-powered web applications using the Vercel AI SDK or LangChain.js.

What is RAG and why does it matter?▾

RAG (Retrieval-Augmented Generation) lets you ground an LLM in your own data by retrieving relevant documents at inference time and passing them into the prompt. It is the standard approach for building accurate, up-to-date AI apps without fine-tuning.

Should I fine-tune a model or use RAG?▾

RAG is better for knowledge-heavy tasks where your data changes frequently. Fine-tuning is better for teaching a model a specific style, format, or specialized reasoning pattern. Most courses explain how to choose between the two approaches.

What cloud platforms are covered?▾

Courses cover AWS (SageMaker, Bedrock), Google Cloud (Vertex AI), Azure OpenAI, and Vercel for serverless AI deployments. Many also cover self-hosted options using Ollama and open-source models like Llama and Mistral.

How is AI engineering different from traditional software engineering?▾

AI engineering deals with probabilistic outputs, prompt design, context windows, token limits, and evaluation strategies that do not exist in traditional software. These courses teach the new mental models and tooling required for building reliable AI systems.