Essential AI Powered Developer Tools Certification

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Overview

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This specialization provides a practical introduction to AI-powered software development, testing, and deployment using leading developer tools such as GitHub Copilot, Amazon Q Developer, Windsurf, and Cursor. Learn to generate, debug, refactor, test, and deploy code, apply prompt engineering, build Python and JavaScript projects, automate CI/CD workflows, and improve software quality and deployment efficiency with Generative AI. By the end of this program, you will be able to: - Master AI Coding Tools: Use GitHub Copilot, Amazon Q Developer, Windsurf, and Cursor for AI-assisted development. - Build and Debug Code: Generate, refactor, debug, and validate code while developing APIs and Python projects. - Improve Software Testing: Generate test cases, optimize regression testing, detect bugs, and enhance testing workflows with GenAI. - Automate Software Deployment: Apply Docker, Terraform, IaC, CI/CD, infrastructure monitoring, and AI-assisted deployment practices. Ideal for beginners, students, developers, programmers, software testers, QA professionals, DevOps professionals, and aspiring AI developers looking to build practical Generative AI and AI-powered developer tool skills.

Syllabus

Course 1: AI Assisted Coding for Developers Training
Course 2: Amazon Q Developer Beginner Training for Python
Course 3: GitHub Copilot JavaScript Testing Training
Course 4: GitHub Copilot Software Deployment Training

Courses

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This certificate for AI Assisted Coding for Developers Training validates your ability to use AI coding tools for modern software development. You demonstrate proficiency in GitHub Copilot, Amazon Q Developer, Windsurf, Cursor, AI prompting, code generation, debugging, refactoring, API development, cloud coding, security reviews, and safe AI assisted development practices.
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Master Amazon Q Developer and prompt engineering for Python development. This course covers Amazon Q Developer setup, AI-assisted coding, prompt engineering, safe prompting, output verification, Python project development, structured workflows, and software testing. Build practical skills through hands-on demos to create, validate, test, and improve reliable Python applications using Amazon Q. By the end of this course, you will be able to: - Set up and use Amazon Q Developer for Python coding - Apply prompt engineering fundamentals and safe prompting - Create structured problem statements for AI-assisted development - Verify AI-generated outputs for accuracy and reliability - Build professional Python projects with structured workflows - Apply unit, integration, and end-to-end testing - Use Amazon Q to support reliable AI-assisted development Ideal for beginners, students, Python developers, programmers, and aspiring AI developers with basic Python knowledge. No prior experience with Amazon Q Developer or prompt engineering is required.
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This comprehensive GitHub Copilot in Software Deployment with JavaScript Training course builds essential skills in AI-assisted deployment, requirements gathering, architecture design, Infrastructure as Code, Docker, CI/CD automation, infrastructure monitoring, and release management. Learn to use Generative AI and GitHub Copilot to optimize deployment workflows while improving speed, efficiency, security, scalability, and reliability. By the end of this course, you will be able to: - Master GenAI for Deployment: Apply GenAI and GitHub Copilot to deployment workflows - Design Deployment Architecture: Select technology stacks and design scalable architectures - Automate Infrastructure: Use Docker, Terraform, and IaC for infrastructure management - Build CI/CD Pipelines: Generate deployment scripts and automate CI/CD workflows - Optimize Deployments: Improve security, scalability, efficiency, and reliability - Monitor Infrastructure: Apply AI-driven monitoring, proactive management, and fault tolerance - Manage Releases: Generate AI-powered release notes and assess deployment outcomes Ideal for beginners, students, developers, and software professionals seeking practical Generative AI, GitHub Copilot, JavaScript, and software deployment skills
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This comprehensive Generative AI for Software Testing Training course builds essential skills in AI-assisted testing, requirement analysis, test planning, test case generation, test data creation, regression testing, and bug detection. Learn to use Generative AI and GitHub Copilot with JavaScript to create, prioritize, execute, and optimize testing workflows while improving coverage, efficiency, quality, and reliability. By the end of this course, you will be able to: - Master GenAI for Testing: Apply Generative AI to modern software testing workflows - Analyze Requirements: Refine requirements and create acceptance criteria using GenAI - Generate Test Cases: Create test cases, scenarios, and synthetic test data with GitHub Copilot - Optimize Test Execution: Improve regression testing, test prioritization, and dynamic testing - Detect Bugs: Use AI-assisted techniques for failure prediction, bug detection, and test cycle closure - Build Practical Skills: Apply GenAI testing through hands-on demos, GitHub Actions, and real-world case studies Ideal for beginners, students, software testers, QA professionals, developers, and aspiring AI testing professionals with basic software testing and JavaScript knowledge who want to build practical Generative AI, GitHub Copilot, and AI-assisted software testing skills.