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Udemy

Amazon Bedrock with Amazon Q Developer-Zero to Hero | Python

via Udemy

Overview

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

Syllabus

  • Introduction
  • Code & Playground - Explore & Relate with it
  • Amazon Q Developer in Lambda
  • Phase 1 - Using Code with different Models for PlayGround
  • Foundation Concepts - Theoretical
  • Phase 2 - Configurations - Inference Parameters
  • Phase 3 - Additional Configurations
  • Bedrock in Console - Safeguards
  • Bedrock Builder Tools - Console
  • Bonus

Taught by

Karan Gupta - Coursediy.com

Reviews

4.8 rating at Udemy based on 133 ratings

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