Certification
Certification in Building LLM Applications with RAG and AI Agents
Get certified in Generative AI app development (LLMs, RAG, Agents). Prove you can build and deploy secure, evaluated chatbots, RAG assistants, and agent workflows; select models, ship low-code prototypes, and deliver measurable ROI.

The exam
Take the certification exam
Multiple-choice questions about the course. Pass with 70% or more and your certificate is issued at once, with a public page and an "Add to LinkedIn" button.
What the exam covers
2 questions from each of the 15 chapters of the course
20 multiple-choice questions, drawn fresh for every attempt. Pass with 70% or more.
- 01Introduction10:25
- 02Interactive session9:34
- 03AI overview and big picture13:21
- 04ML and deep learning13:18
- 05Large language models12:30
- 06Recap and Q&A6:42
- 07Neural networks and the future of work12:40
- 08Coding requirements11:01
- 09Demo: using LLMs18:38
- 10Demo: CrewAI11:31
- 11Skills to enter AI14:41
- 12Data foundations and careers11:31
- 13System requirements and course plan16:29
- 14AI's impact on employment16:47
- 15Bonus and final Q&A7:20
Generative AI Essentials & Projects: Build LLM Apps, RAG, Agents (Video Course) is a hands-on certification that takes you from your first prompt to shipping production-grade AI apps, chatbots, RAG assistants, and agent teams,no PhD required.
You'll gain Increased Productivity, Competitive Advantage, a Future-Proof Career, Improved Decision-Making, Higher Income Potential, and Adaptability and Growth by learning to choose the right models, build low-code prototypes, add security and evals, and deliver measurable ROI.
Enroll now to turn ideas into deployed AI systems that advance your career and impact.
This certification covers the following topics:
- LLM fundamentals and the model marketplace: how to evaluate and choose the right model
- Prompt engineering and system prompting best practices
- Low-code prototyping and app development for chatbots and copilots
- Retrieval-Augmented Generation (RAG): data pipelines, indexing, and grounding
- Agentic workflows: single-agent and multi-agent orchestration to get work done
- Security, privacy, and risk management for AI applications
- Evals, monitoring, and quality assurance for reliable LLM outputs
- From prototype to production: deployment patterns, CI/CD, and MLOps
- Hardware and infrastructure essentials for cost, latency, and scale
- Real-world use cases and ROI-driven implementation patterns
- Governance, ethics, and human oversight for responsible AI
- Career paths, in-demand skills, and portfolio projects to showcase
Jobs this certification suits
Our AI checked this certification against 500 jobs; these get the most out of it. Each job links to its learning path.