Generative AIIntermediate
Generative AI Systems with Amazon Bedrock
Construct enterprise-grade Retrieval Augmented Generation (RAG) applications using Claude, Llama 3, and vector embeddings.
- Estimated duration
- 4 Weeks
- Skill level
- Intermediate
- Curriculum
- 4 modules
- Recommended for
- AI/ML Enthusiasts & Final Year Project Teams
Learning objectives
By the end of this path, you will be able to:
- Bedrock Converse API and prompt engineering guardrails
- Chunking documents & generating vectors with Amazon Titan
- Vector indexing in OpenSearch Serverless and pgvector on RDS
- Building full-stack AI streaming chat UIs with Next.js
Curriculum
- 1
Bedrock Converse API and prompt engineering guardrails
- 2
Chunking documents & generating vectors with Amazon Titan
- 3
Vector indexing in OpenSearch Serverless and pgvector on RDS
- 4
Building full-stack AI streaming chat UIs with Next.js
Practice with hands-on projects
Suggested projects from the GCET project lab that reinforce this path's skills.
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