Generative AI & RAG Engineering Certification
Engineer grounded, production-grade LLM applications with retrieval
Key facts
- Level: Professional
- Field: Artificial Intelligence & LLMs
- Estimated study time: about 30 hours
- Credential price: $149
- Exam: 66 questions · 90 minutes · pass mark 75%
About the Generative AI & RAG Engineering certification
Master the engineering discipline behind production generative-AI systems built on large language models. This professional certification starts with how you steer a model at inference time: prompting techniques (zero-shot, few-shot, chain-of-thought), system prompts and role design, and the decoding parameters — temperature, top-k, top-p — that trade determinism for diversity. The core of the course is Retrieval-Augmented Generation (RAG) end to end: loading and chunking documents (size, overlap, and semantic strategies), embedding text for retrieval, storing vectors in a vector database with the right index (HNSW, IVF), and measuring similarity with cosine and dot product. You will go deep on retrieval itself — dense vectors, sparse/BM25 lexical search, hybrid fusion, and reranking with cross-encoders — then assemble a context window that respects token budgets and avoids the lost-in-the-middle failure mode. The final third is what separates demos from products: grounding answers with citations, diagnosing and mitigating hallucination, evaluating a RAG pipeline for faithfulness and answer relevance (RAGAS), wiring function/tool calling and structured JSON output, adding guardrails and safety filters, and controlling cost with caching. By the end you can design, build, evaluate, and debug a grounded RAG application and defend every architectural choice against the alternatives.
What you will learn
The official Generative AI & RAG Engineering study course covers:
- Prompting & Decoding Control — Steer an LLM at inference time: zero/few-shot and chain-of-thought prompting, system prompts, and the decoding dials — temperature, top-k, top-p.
- The RAG Pipeline End to End — The full architecture: offline ingest (load, chunk, embed, index) and online query (embed, retrieve, rerank, generate), plus chunking strategy.
- Vector Databases & Retrieval — Storing and searching embeddings: HNSW and IVF indexes, similarity metrics, and dense vs sparse vs hybrid retrieval with reranking.
- Grounding, Hallucination & Evaluation — Context-window assembly, hallucination causes and mitigation, citations, and measuring RAG quality with faithfulness, relevance, and RAGAS.
- Tools, Structured Output, Guardrails & Cost — Function/tool calling, structured JSON output, guardrails and safety against prompt injection, and controlling latency and cost with caching.
Prerequisites
Frequently asked questions
- Is the Generative AI & RAG Engineering certificate verifiable?
- Yes. Every issued Hootix Academy certificate carries a unique credential code that anyone can verify online.
- How is the Generative AI & RAG Engineering exam structured?
- It is a 90-minute proctored multiple-choice exam of 66 questions; you need 75% to pass.
- Do I need to buy the course to take the exam?
- You can purchase the certification exam on its own, or bundle it with the full study course at a reduced price.
- How long does the Generative AI & RAG Engineering course take?
- About 30 hours of self-paced study.