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Certification: Generative AI Development Skills for Developers

Show the world you have AI skills with this certification, designed to help developers master generative AI tools and techniques. Build real-world projects, boost your expertise, and add a future-ready credential to your CV.

Exam of 10 to 20 questionsCertificate for LinkedInIntermediate · Expert · Technical
IT and development
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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.

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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.

  1. 01Introduction and the GenAI pipeline85:12
  2. 02Data representation and vectorisation63:45
  3. 03Text classification, LLMs and transformers87:05
  4. 04Hands-on Hugging Face91:11
  5. 05OpenAI API and Telegram bot111:09
  6. 06Prompt engineering and vector DBs96:23
  7. 07Pinecone, Weaviate and LangChain97:15
  8. 08Interview questions creator57:26
  9. 09Website chatbot and Llama103:15
  10. 10Falcon, RAG and fine-tuning76:14
  11. 11LlamaIndex, Mistral and stock analysis54:56
  12. 12Medical chatbot70:47
  13. 13Source code analysis and Zomato bot65:33
  14. 14CI/CD on AWS and LLMOps93:25
  15. 15Vertex AI and Gemini Pro117:45
About the course

The Certification: Generative AI Development Skills for Developers provides a comprehensive pathway for developers to master the essential tools and techniques in generative AI. By completing this certification, you’ll gain an edge through advanced skills such as increased productivity, improved decision-making, and adaptability in a rapidly evolving field. Enroll today to unlock new career opportunities and elevate your expertise in AI development.

This certification covers the following topics:

  • Advanced Text Analysis
  • Word Embeddings (Word2Vec)
  • Transformer Architecture and Self-Attention
  • Vector Databases (ChromaDB, Pinecone, FAISS, AWS Bedrock)
  • Retrieval Augmented Generation (RAG)
  • QA System with Gemini Pro and Langchain
  • Using LlamaIndex for Document Loading
  • Local LLMs (Llama 2) with Langchain
  • Hugging Face Transformers with Langchain
  • RAG with Vertex AI Platform
  • Chainlit for Building UIs
  • Practical Applications of Generative AI
  • Ethical Considerations in Using Generative AI