Written by the AgileFever editorial team. Program details were checked against the live program pages in October 2026. We run both programs, so read this as a vendor comparison and check the claims against the program pages.
The two programs share a name stem and about 70 hours of teaching, and people often ask which is the “real” one. They are different courses for different starting points. One is a broad generative AI engineering course. The other is a narrower, later-stage course about agents.
The programs side by side
| Gen AI BootCamp | GenAI and Agentic AI BootCamp | |
|---|---|---|
| Price (US) | $1,600 | $2,000 |
| Length | 72 hours over 9 weeks, as listed on the program page | 74 hours over 8 weeks (64+ live, 10 self-paced) |
| Curriculum | 12 modules, from Python and deep learning to deployment and safety | 17 live modules plus a recorded n8n module |
| Projects | 9 projects plus a choice of 3 capstones (LegalBot, AI Tutor, Resume Screener) | 10+ projects, 8 capstone options, 2 built live |
| Agents | Not a focus | The main focus: LangGraph, CrewAI, AutoGen, memory, multi-agent work |
| Fine-tuning | LoRA, QLoRA and PEFT, with a ticket-classification project | LoRA and QLoRA, and when to choose RAG instead |
| Image and video generation | A full module (diffusion, ControlNet basics) | Multimodal and document intelligence, mostly OCR and extraction |
| Built for | Python developers, ML engineers, data scientists, data analysts, AI engineers | Experienced IT professionals who can read and write code |
Additional discounts are available. Contact us to know more.
What each one teaches
The Gen AI BootCamp starts lower in the stack. Its first three modules cover Python, deep learning (ANN, CNN, RNN, LSTM) and NLP basics, so you meet embeddings and sequence models before you meet an LLM. Modules four to nine cover generative model families, prompt patterns, how GPT, LLaMA, Claude and Gemini differ, RAG with FAISS, Pinecone and Weaviate, fine-tuning, and text-to-image tools. The last three cover coding assistants, deployment with Streamlit, Gradio and Docker, and safety topics such as prompt injection and hallucination control.
The GenAI and Agentic AI BootCamp assumes you can already code. It spends four modules on foundations (prompting, advanced RAG, fine-tuning, document intelligence), eight on building agents, and five on production and enterprise work such as deployment, security, and building agents on Azure. It does not teach neural network basics or GAN and diffusion models.
Rough grouping of listed modules, our own categorisation of the program pages
Which one fits your situation
| Your situation | Better fit | Why |
|---|---|---|
| Data scientist or ML engineer who wants to move into LLM work | Gen AI BootCamp | You get the model-side material: fine-tuning, embeddings, evaluation |
| Backend, full stack or cloud engineer with solid Python | GenAI and Agentic AI BootCamp | You skip the neural-network groundwork and go straight to agent design and deployment |
| Data analyst with little Python | Neither yet | Take Python for AI first, then the Gen AI BootCamp |
| Team lead who needs to judge agent proposals, not build them | Neither | A role-based course is a shorter and cheaper route |
| You want to ship an internal agent in the next quarter | GenAI and Agentic AI BootCamp | Agents, memory, security and deployment are the core of the syllabus |
Check these before you enroll
The Gen AI BootCamp page is not fully consistent with itself. The headline says 72 hours, one FAQ answer says 70, and the page says anyone can register while the “built for” list names developers, ML engineers and data professionals. Treat the hours as roughly 70 to 72 and ask an advisor for the current prerequisite. If you cannot write a loop and call an API in Python today, plan on the 6-hour Python for AI course first.
Both programs record live sessions, so a missed class is recoverable. Neither is a quick course: 8 to 9 weeks means a few evenings or a weekend block every week, plus project time.
When to choose something else
- If you want to build classical machine learning models for prediction and classification, read our AI and ML BootCamp comparison.
- If your work is running models in production, the MLOps, LLMOps and Agentic AI Ops BootCamp (60 live hours, $2,000) is closer.
- If you only need to use AI tools well in your current role, the 12 to 16 hour role-based courses at $450 are enough.
