AI BootCamps (5 Courses)
Career Oriented
Course Category Career Oriented
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Generative AI is moving from experiments to real products. Companies now need engineers who can build reliable LLM applications, not just use AI tools. This bootcamp focuses on the engineering side of GenAI.
You will learn to design prompts, build RAG pipelines, fine-tune models, and develop real AI applications. By the end, you’ll be able to build production-ready LLM systems like enterprise knowledge assistants.
Go beyond prompt engineering, learn how LLMs actually work and how to optimize them for real application
Build advanced RAG systems that retrieve, reason, and generate answers from large knowledge bases
Fine-tune large language models using LoRA and parameter-efficient techniques
Design enterprise AI assistants capable of document search, summarization, and knowledge retrieval
Work with multimodal AI systems combining text and image intelligence
Evaluate and improve AI outputs by detecting hallucinations and benchmarking prompts
Complete hands-on 8 labs, 3 projects and end-to-end capstone
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To fast-track your career and achieve
Name of Exam – AgileFever Advanced Generative AI BootCamp
Exam details are as follows:
Yes, basic programming knowledge and some familiarity with Python is expected. This is an advanced course — it covers transformer internals, LoRA fine-tuning, and RAG engineering, not AI basics. If you’ve used LLM APIs or tools before, you’re in the right place.
100% live, instructor-led training. Every session is real-time with an instructor — no recordings, no self-paced modules. You ask questions, get answers, and work through labs on the spot.
You’ll be able to build production-grade LLM applications — RAG pipelines, fine-tuned domain-specific models, and enterprise AI assistants for document search and knowledge retrieval.
You’ll work hands-on with OpenAI, LangChain, LlamaIndex, Hugging Face, Pinecone, and FAISS — the tools actively used in GenAI engineering roles today.
Yes. A course completion certificate is issued by AgileFever upon successfully completing all modules, labs, projects, and the capstone.
Roles like GenAI Engineer, LLM Engineer, AI Application Developer, and ML Engineer with GenAI specialization.
This goes well beyond prompts. You’ll learn how LLMs work under the hood, build and optimize RAG systems, fine-tune models, detect hallucinations, and ship production-ready applications — skills that basic courses don’t cover.