Certification
Certification in Building and Deploying Generative AI Solutions with LLMs
Become certified in Generative AI and Large Language Models and demonstrate the ability to build, implement, and optimize AI-powered solutions, turning theory into practical tools for smarter workflows and innovative business applications.
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.
- 01Introduction to generative AI and LLMs10:36
- 02Exploring and comparing LLMs20:58
- 03Using generative AI responsibly9:20
- 04Prompt engineering fundamentals23:14
- 05Advanced prompts16:58
- 06Text generation applications15:31
- 07Chat applications13:33
- 08Search apps with vector databases17:58
- 09Image generation applications22:24
- 10Low-code AI applications16:23
- 11Function calling and UX21:43
- 12Security and the app lifecycle20:34
- 13RAG and vector databases22:20
- 14AI agents7:54
- 15Fine-tuning LLMs20:51
The "Microsoft Developer Series: Generative AI and LLMs Fundamentals for Beginners (Video Course)" certification introduces the essential concepts and practical skills needed to understand and use Generative AI and Large Language Models effectively. By completing this course, you will gain valuable techniques that can boost your productivity, enhance your adaptability, and position you for future career growth in the evolving field of AI. Enroll today to build a strong foundation and confidently apply AI solutions in your work and projects.
This certification covers the following topics:
- Core principles of Generative AI and Large Language Models (LLMs)
- The evolution of AI: from early chatbots to modern generative systems
- How large language models work and their underlying mechanisms
- Differences between foundation models and LLMs
- Types of language models for text, images, and other data
- Prompt engineering: guiding AI responses effectively
- Key techniques for building generative AI applications
- Architecture and deployment options: service vs. model, open source vs. proprietary
- Customizing and augmenting models for specific needs
- Responsible AI practices, security, and risk mitigation
- Managing the lifecycle of LLM applications (LLMOps)
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.