AI & Generative AI
LLMs, embeddings, prompting, retrieval-augmented generation and building with AI responsibly.
What you are tested on
- How LLMs work
- Prompt design
- Embeddings and vector search
- RAG applications
- Evaluation and safety
Practice problems
Roadmaps
AI & Generative AI Roadmap
From how language models work to shipping a safe, grounded AI feature — the practical path for a developer.
AI Engineer Roadmap: Building LLM Apps
Learn to build reliable LLM-powered applications: prompting, RAG, agents and evaluation, step by step.
Prompt Engineering Roadmap
Learn to get dependable results from language models: clear instructions, examples, structured output and honest evaluation.
Building AI Agents and RAG Apps Roadmap
Go beyond chat: give a model tools and your own data, and learn how to keep the result reliable and affordable.
AI-Assisted Software Development Roadmap
Use coding assistants to ship faster without losing the fundamentals employers still test for.
Generative AI Engineer Roadmap
Build reliable products on top of language models: prompts, retrieval, agents and evaluation.
How your AI & Generative AI rating works
You start at 1200. Each timed, rated test moves your AI & Generative AI rating up or down, the way chess ratings move. Recruiters see the number and the band (Beginner, Intermediate, Advanced or Expert), so they can judge your skill before reading a résumé. See a sample profile.
Questions about AI & Generative AI
Do I need to know ML to build with LLMs?
Not deeply. Strong programming, APIs and clear thinking about data and evaluation matter more at the start.
How do I show GenAI skill?
Build one small working app, explain its limits, and take a rated test for a verifiable number.