Event 3

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Event Report: AWS Cloud Mastery Series #1 — AI/ML/GenAI on AWS

Provide an overview of the AI/ML landscape in Vietnam.
Introduce key AWS AI/ML services, especially Amazon SageMaker.
Dive into Generative AI with Amazon Bedrock, covering foundation models and modern deployment techniques (RAG, Prompt Engineering).

Overview: context of AI/ML in Vietnam and the workshop objectives.
Amazon SageMaker: AWS’s end-to-end ML platform.
ML workflow: data preparation, labeling, training, tuning, and model deployment.
Built-in MLOps capabilities.
Live demo: walkthrough of SageMaker Studio.

Foundation Models: comparison and guidance for choosing models such as Claude, Llama, Titan, etc.
Prompt Engineering:
- Advanced techniques: Chain-of-Thought reasoning, Few-shot learning.
Retrieval-Augmented Generation (RAG):
- RAG architecture and integration with external knowledge bases.
Bedrock Agents: building multi-step workflows and tool integrations.
Guardrails: safety and content filtering principles.
Live demo: building a Generative AI chatbot using Bedrock.

SageMaker: understood as a comprehensive platform that manages the entire ML lifecycle (data prep → training → deployment).
Bedrock & GenAI: learned Bedrock’s role as a foundation-model management platform, how to compare FMs, and core techniques like Prompt Engineering and RAG.
Project application: RAG and Bedrock Agents are useful for enhancing AI/chatbot features in the Travel-Guided project.
Live demos provided practical insights into deployment flows and rapid prototyping with Bedrock.