Udemy – Amazon Bedrock with Amazon Q Developer-Zero to Hero | Python
English | Tutorial | Size: 3.55 GB
Code Amazon Bedrock with Amazon Q Developer in Lambda using Python (Boto3). Use Q as Co-Pilot to code. Novice to Expert
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
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