Published 11/2024
Created by Karan Gupta
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 71 Lectures ( 7h 2m ) | Size: 3.54 GB
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
Requirements
Basic Understanding of Coding – Python is required
From Basics to Details: We start from the fundamentals of AI/ GenAI/ AWS / Amazon Q, explaining core concepts and terminology in a clear and concise manner.
An AWS account
Basic understanding of cloud computing concepts (helpful but not mandatory)
Enthusiasm to learn about AI and its practical applications
Hands-On Learning: Hands-on labs and exercises are provided throughout the course to reinforce learning and allow you to practice what you’ve learned in a real-world environment.
Description
Master Generative AI Development with Amazon Bedrock & Amazon QCourse OverviewDive 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 LearnSet up and configure Amazon Bedrock for AI model deploymentIntegrate foundation models like Claude, Llama 2, and Amazon TitanDevelop with Amazon Q’s AI-assisted coding capabilitiesBuild production-ready applications using AWS AI servicesImplement best practices for prompt engineering and AI safetyCreate scalable and cost-effective AI solutionsCourse ContentSection 1: Getting Started with Amazon BedrockIntroduction to Amazon Bedrock architectureSetting up your development environmentUnderstanding foundation models and their capabilitiesAPI integration and authenticationSection 2: Building with Foundation ModelsText generation and completionImage generation and manipulationCode generation and optimizationFine-tuning models for specific use casesSection 3: Amazon Q Developer ExperienceAI-assisted code developmentCode review and optimizationDocumentation generationSecurity best practices implementationSection 4: Inference Parameters Code with Q for BedrockBuilding a code with AI assistantCreating an AI-powered content generatorDeveloping an image generation applicationImplementing a code refactoring systemSection 5: Additional Configuration for ModelsSystem PromptsMax LengthStop SequenceGuardrails and Builder ToolsPrerequisitesBasic understanding of Python programmingFamiliarity with AWS servicesAWS account with appropriate permissionsWho This Course is ForSoftware developers looking to integrate AI into their applicationsCloud engineers wanting to expand their AWS AI expertiseTechnical leads evaluating AI solutions for their organizationsDevOps 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