Event 2

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

Provide an overview of the AI/ML landscape in Vietnam.
Introduce core AWS AI/ML services, with a strong focus on Amazon SageMaker.
Explore Generative AI using Amazon Bedrock, covering foundation models and modern techniques such as RAG and Prompt Engineering.

Introduction to the AI/ML context in Vietnam and objectives of the workshop.
Amazon SageMaker: AWS’s end-to-end platform for building and operating ML solutions.
Machine learning workflow: data preparation, labeling, training, tuning, and model deployment.
Built-in MLOps features within SageMaker.
Live demonstration: guided walkthrough of SageMaker Studio.

Foundation Models: comparison and guidelines for selecting models such as Claude, Llama, Titan, and others.
Prompt Engineering:
- Advanced methods including Chain-of-Thought reasoning and Few-shot learning.
Retrieval-Augmented Generation (RAG):
- RAG architecture and integration with external knowledge sources.
Bedrock Agents: building multi-step workflows and enabling tool integrations.
Guardrails: best practices for safety controls and content filtering.
Live demo: creating a Generative AI chatbot using Bedrock.

SageMaker: gained a clear understanding of its role as a complete platform for the ML lifecycle (data preparation → training → deployment).
Bedrock & GenAI: learned how Bedrock manages foundation models, how to evaluate different FM options, and the relevance of techniques such as Prompt Engineering and RAG.
Project application: both RAG and Bedrock Agents provide valuable enhancements for the AI/chatbot features in the Travel-Guided project.
Live demos offered practical insights into deployment flows and rapid prototyping with Bedrock.

The live demos—especially the quick setup of a Bedrock-based chatbot—were particularly impressive.
The event provided excellent opportunities to network and exchange knowledge with AI/ML professionals in Vietnam.