AI | GenAI | AWS | Amazon Q Developer | Your CoPilot | 2025

Overview

Includes Working on AWS Console, IDE, Slack Integration, CLI | AWS Certified AI Practitioner | Optimise code on clicks What you'll learn:

Master Amazon Q Developer setup and integrationDevelop effective code generation skills using AIOptimize AWS service utilization with Amazon QEnhance debugging and troubleshooting capabilitiesAccelerate documentation processes using AI assistanceImplement AI-driven security best practicesOptimize code performance with Amazon Q insightsImprove collaborative development workflowsCustomize Amazon Q for specific project needsApply AI-assisted coding to real-world scenariosDeepen AWS ecosystem integration knowledgeAdopt ethical AI practices in software development "Master Amazon Q Developer:

AI-Powered Coding for AWS Ecosystems"Unlock the full potential of AI-assisted development with our comprehensive Amazon Q Developer course. This cutting-edge program is designed for developers, software engineers, and AWS professionals looking to supercharge their productivity and innovation within the AWS ecosystem.Course Overview:

In this hands-on course, you'll dive deep into Amazon Q Developer, learning how to leverage its AI capabilities to streamline your coding process, enhance problem-solving, and accelerate project delivery.

From code generation to debugging and optimization, you'll discover how Amazon Q Developer can transform your development workflow.What You'll Learn:

Amazon Q Developer Fundamentals:

Understanding the AI technology behind Amazon QSetting up and configuring Amazon Q in your development environmentBest practices for integrating Amazon Q into your workflowAI-Assisted Coding:

Generating code snippets and entire functions with natural language promptsUtilizing Amazon Q for code completion and suggestionsAdapting Amazon Q's output to match your coding style and project requirementsAWS Service Integration:

Leveraging Amazon Q to navigate and implement AWS servicesGenerating AWS CloudFormation templates and Infrastructure as CodeOptimizing AWS resource usage with AI-powered suggestionsDebugging and Troubleshooting:

Using Amazon Q to identify and fix code errorsAI-assisted log analysis and error tracingGenerating test cases and improving code coverageDocumentation and Knowledge Management:

Automating code documentation with Amazon QCreating and maintaining wikis and internal knowledge basesEnhancing code readability and maintainabilitySecurity and Best Practices:

Implementing secure coding practices with Amazon Q's guidanceIdentifying potential vulnerabilities in your codeEnsuring compliance with industry standards and AWS best practicesPerformance Optimization:

Using Amazon Q to optimize code performanceIdentifying bottlenecks and suggesting improvementsScaling applications efficiently within the AWS environmentCollaborative Development:

Integrating Amazon Q into team workflowsEnhancing code reviews and pair programming sessionsStandardizing coding practices across teamsReal-World Applications:

Throughout the course, you'll work on practical, real-world projects that simulate actual development scenarios. You'll learn how to:

Rapidly prototype new features and applicationsRefactor and modernize legacy codeImplement complex AWS architectures with easeAutomate routine coding tasks to focus on high-value developmentBy the end of this course, you'll be equipped to:

Significantly reduce development time and increase productivityWrite more efficient, secure, and maintainable codeSeamlessly integrate AI assistance into your daily coding practicesLeverage the full power of AWS services in your applicationsStay ahead of the curve in the rapidly evolving field of AI-assisted developmentWhether you're a seasoned AWS developer or new to the ecosystem, this course will empower you to take your coding skills to the next level with Amazon Q Developer.

Join us and become a pioneer in the future of AI-augmented software development!"

Syllabus

• Introduction to Amazon Q Developer
Overview of AI-Powered Coding
Importance in AWS Ecosystems
Course Objectives and Outcomes
• Fundamentals of Artificial Intelligence
Core AI Concepts
Machine Learning Essentials
Overview of Generative AI (GenAI)
• Overview of AWS Ecosystems
Key AWS Services and Tools
Cloud Infrastructure Basics
Integration of AI with AWS
• Getting Started with Amazon Q Developer
Installation and Setup
Basic Navigation and Features
Understanding the Q Console
• Mastering AI-Powered Coding with Amazon Q
AI-Driven Code Assistance
Code Generation Techniques
Debugging and Efficiency Optimization
• Practical Applications of Amazon Q Developer
Real-World Use Cases
Project Development in AWS
Utilization in Data Analysis and Processing
• Advanced Amazon Q Developer Features
Customization and Extension
Integrating Other AWS AI Services
Security and Compliance in AI Projects
• Collaborative Development with Your CoPilot
Using Amazon Q for Team Projects
Workflow Optimization
Best Practices for Collaborative AI Development
• Future Trends and Innovations
AI Evolution in AWS Ecosystems
Industry Trends and Future Applications
Preparing for AI Advancements
• Conclusion and Resources
Course Summary
Additional Learning Resources
Certification and Further Opportunities

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Taught by

Karan Gupta

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Subjects

Programming