Amazon Bedrock với Amazon Q Developer - Từ Cơ Bản đến Chuyên Gia | Python

Master Generative AI Development with Amazon Bedrock & Amazon Q

Course Overview

Dive into the cutting-edge world of generative AI development using Amazon's latest tools - Amazon Bedrock and Amazon Q. This comprehensive course will teach you how to build, deploy, and optimize AI-powered applications using Amazon's most advanced AI services.

What You'll Learn

• Set up and configure Amazon Bedrock for AI model deployment

• Integrate foundation models like Claude, Llama 2, and Amazon Titan

• Develop with Amazon Q's AI-assisted coding capabilities

• Build production-ready applications using AWS AI services

• Implement best practices for prompt engineering and AI safety

• Create scalable and cost-effective AI solutions

Course Content

Section 1: Getting Started with Amazon Bedrock

• Introduction to Amazon Bedrock architecture

• Setting up your development environment

• Understanding foundation models and their capabilities

• API integration and authentication

Section 2: Building with Foundation Models

• Text generation and completion

• Image generation and manipulation

• Code generation and optimization

• Fine-tuning models for specific use cases

Section 3: Amazon Q Developer Experience

• AI-assisted code development

• Code review and optimization

• Documentation generation

• Security best practices implementation

Section 4: Inference Parameters Code with Q for Bedrock

• Building a code with AI assistant

• Creating an AI-powered content generator

• Developing an image generation application

• Implementing a code refactoring system

Section 5: Additional Configuration for Models

• System Prompts

• Max Length

• Stop Sequence

• Guardrails and Builder Tools

Prerequisites

• Basic understanding of Python programming

• Familiarity with AWS services

• AWS account with appropriate permissions

  
  

Who This Course is For

• Software developers looking to integrate AI into their applications

• Cloud engineers wanting to expand their AWS AI expertise

• Technical leads evaluating AI solutions for their organizations

• DevOps engineers interested in AI infrastructure