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Amazon Bedrock with Amazon Q Developer-Zero to Hero | Python | Udemy
English | Size: 3.55 GB
Genre: eLearning[/center]

Code Amazon Bedrock with Amazon Q Developer in Lambda using Python (Boto3). Use Q as Co-Pilot to code. Novice to Expert

What you'll learn
Master the fundamentals of generative AI and its business applications
Navigate the Amazon Bedrock console with confidence
Master Amazon Q Developer setup and integration
Create custom images with AI using simple text prompts
Optimize AWS service utilization with Amazon Q
Develop effective code generation skills using AI
Optimize code performance with Amazon Q insights
Improve collaborative development workflows
Implement responsible AI practices and ethical considerations
Complete hands-on, real-world AI projects using Amazon Bedrock

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

Who this course is for:
For Beginners: Individuals with little to no experience in AI/ GenAI/ AWS / Amazon Q. Fresh graduates or students looking to kickstart their careers in AI/ GenAI/ AWS / Amazon Q or software development.
Everyone can pick up this course, at their own pace.
For Intermediate Users: Professionals who have some familiarity with AI but want to deepen their understanding and skills. Developers or sysadmins who have worked with AI in basic capacities but seek to expand their knowledge and capabilities.
For Advanced Users: Experienced AI engineers, software architects, or team leads who want to refine their AI skills and stay updated with the latest best practices.
For Career Changers: Individuals transitioning from other IT roles (such as system administration, software development, or quality assurance) to AI / GenAI / Amazon Q

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