What core areas does this specialization cover?

The program covers AI-assisted coding, software testing, software deployment, prompt engineering, code generation, debugging, refactoring, test automation, containerization, CI/CD, infrastructure management, and AI-powered development workflows.

What will I be able to do after completing this specialization?

You will be able to generate, debug, refactor, test, optimize, and deploy software using Generative AI and leading AI-powered developer tools.

Does the specialization include hands-on learning?

Yes. The program emphasizes practical learning through hands-on demonstrations, coding projects, testing workflows, deployment exercises, and real-world AI-assisted development scenarios.

Does the specialization cover AI-powered developer tools?

Yes. The program focuses on GitHub Copilot, Amazon Q Developer, Windsurf, and Cursor to help learners improve coding, testing, deployment, and software development workflows.

Will I receive a certificate after completion?

Yes. You will earn the Essential AI-Powered Developer Tools Certification, validating your proficiency in Generative AI, AI-assisted software development, testing, deployment, and modern AI-powered developer tools.

Is this course really 100% online? Do I need to attend any classes in person?

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

Can I just enroll in a single course?

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Can I take the course for free?

No, you cannot take this course for free. When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you cannot afford the fee, you can apply for financial aid.

Will I earn university credit for completing the Specialization?

This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

Spezialisierung „Essential AI Powered Developer Tools Certification“

Eignen Sie sich gefragte Fähigkeiten mit einem ganzjährigen Coursera Plus-Abonnement an -- jetzt für 239 $. Sparen Sie jetzt.

spezialisierung ist nicht verfügbar in Deutsch (Deutschland)

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Spezialisierung „Essential AI Powered Developer Tools Certification“

AI Powered Developer Tools.

Dozent: Priyanka Mehta

Bei Mehr erfahren enthalten

4-teilige Kursreihe

Befassen Sie sich eingehend mit einem Thema

Stufe Anfänger

Keine Vorkenntnisse erforderlich

4 Wochen zu vervollständigen

unter 10 Stunden pro Woche

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

4-teilige Kursreihe

Befassen Sie sich eingehend mit einem Thema

Stufe Anfänger

Keine Vorkenntnisse erforderlich

4 Wochen zu vervollständigen

unter 10 Stunden pro Woche

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

Was Sie lernen werden

Master AI coding tools like GitHub Copilot, Amazon Q Developer, Windsurf, and Cursor
Generate, debug, refactor, test, and validate code with Generative AI
Build efficient software testing workflows with AI-assisted test generation and regression optimization
Automate deployment using Docker, Terraform, IaC, CI/CD, and AI-powered monitoring

Kompetenzen, die Sie erwerben

Kategorie: Application Programming Interface (API)
Kategorie: Regression Testing
Kategorie: Application Deployment
Kategorie: Prompt Engineering
Kategorie: Test Automation
Kategorie: Generative AI
Kategorie: Infrastructure as Code (IaC)
Kategorie: Unit Testing
Kategorie: Code Review
Kategorie: Containerization
Kategorie: Responsible AI
Kategorie: CI/CD
Kategorie: Software Testing
Kategorie: Requirements Analysis
Kategorie: Software Development
Kategorie: AI Workflows

Werkzeuge, die Sie lernen werden

Kategorie: Docker (Software)
Kategorie: Javascript
Kategorie: Software Engineering Tools
Kategorie: Terraform

Wichtige Details

Zertifikat zur Vorlage

Zu Ihrem LinkedIn-Profil hinzufügen

Unterrichtet in Englisch

Kürzlich aktualisiert!

September 2026

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Erweitern Sie Ihre Fachkenntnisse.

Erlernen Sie gefragte Kompetenzen von Universitäten und Branchenexperten.
Erlernen Sie ein Thema oder ein Tool mit echten Projekten.
Entwickeln Sie ein fundiertes Verständnisse der Kernkonzepte.
Erwerben Sie ein Karrierezertifikat von Simplilearn.

Spezialisierung - 4 Kursreihen

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.

Übungsprojekt

Project Overview: Build, Test, and Deploy a Secure Customer Feedback API

In this project, you'll take a Customer Feedback API from requirements to deployment using AI coding assistants. You'll use AI to accelerate coding, testing, debugging, and deployment while applying human review, validation, and security practices throughout the development process.

Project tasks include:

- Define API Requirements and Acceptance Criteria

- Build the API Using AI Coding Assistants

- Implement Input Validation

- Create and Debug Automated Tests

- Containerize the API with Docker

- Set Up CI/CD Testing

- Create Infrastructure as Code

- Conduct a Security and Deployment Readiness Review

AI Assisted Coding for Developers Training

KURS 1, 12 Stunden

Was Sie lernen werden

Master GitHub Copilot, Amazon Q Developer, Windsurf, and Cursor
Generate, debug, refactor, and validate code with AI
Build APIs and streamline AI-assisted development workflows
Apply secure, responsible, and effective AI coding practice

Kompetenzen, die Sie erwerben

Kategorie: GitHub Copilot

Kategorie: Computer Programming Tools

Kategorie: Verification And Validation

Kategorie: Application Programming Interface (API)

Kategorie: Amazon Web Services

Kategorie: Responsible AI

Kategorie: Software Development

Kategorie: Amazon S3

Kategorie: Software Engineering Tools

Kategorie: Secure Coding

Kategorie: Software Development Tools

Kategorie: Cloud Development

Kategorie: Agentic systems

Kategorie: Prompt Engineering

Kategorie: Debugging

Kategorie: Agentic Workflows

Kategorie: Code Review

Kategorie: AI Workflows

Amazon Q Developer Beginner Training for Python

KURS 2, 6 Stunden

Was Sie lernen werden

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.

Kompetenzen, die Sie erwerben

Kategorie: AI Workflows

Kategorie: AI Enablement

Kategorie: Software Testing

Kategorie: Verification And Validation

Kategorie: Python Programming

Kategorie: Unit Testing

Kategorie: Prompt Engineering

Kategorie: Engineering

Kategorie: Responsible AI

Kategorie: Application Development

Kategorie: Software Development

GitHub Copilot JavaScript Testing Training

KURS 3, 14 Stunden

Was Sie lernen werden

Master GenAI for software testing with GitHub Copilot
Analyze requirements and generate test cases and scenarios
Optimize test data, regression testing, and test execution
Detect bugs and improve testing efficiency with AI-assisted workflows

Kompetenzen, die Sie erwerben

Kategorie: Software Testing

Kategorie: Scenario Testing

Kategorie: Javascript

Kategorie: Test Planning

Kategorie: User Story

Kategorie: Regression Testing

Kategorie: Generative AI

Kategorie: Test Data

Kategorie: Test Automation

Kategorie: AI literacy

Kategorie: Requirements Analysis

Kategorie: GitHub

Kategorie: Test Case

GitHub Copilot Software Deployment Training

KURS 4, 17 Stunden

Was Sie lernen werden

Generate release notes efficiently using GitHub Copilot and GenAI
Apply GenAI to streamline software release management
Analyze real-world implementation challenges and business outcomes
Assess the impact of AI-assisted release workflows on deployment efficiency

Kompetenzen, die Sie erwerben

Kategorie: Infrastructure as Code (IaC)

Kategorie: IT Infrastructure

Kategorie: Software Architecture

Kategorie: Continuous Integration

Kategorie: Docker (Software)

Kategorie: Generative AI

Kategorie: CI/CD

Kategorie: Containerization

Kategorie: System Monitoring

Kategorie: Architecture and Construction

Kategorie: Application Deployment

Kategorie: AI Workflows

Kategorie: Terraform

Kategorie: Release Management

Erwerben Sie ein Karrierezertifikat.

Fügen Sie dieses Zeugnis Ihrem LinkedIn-Profil, Lebenslauf oder CV hinzu. Teilen Sie sie in Social Media und in Ihrer Leistungsbeurteilung.

Dozent

Priyanka Mehta

Simplilearn

109 Kurse96.139 Lernende

von

Simplilearn

Warum entscheiden sich Menschen für Coursera für ihre Karriere?

Felipe M.

Lernender seit 2018

„Es ist eine großartige Erfahrung, in meinem eigenen Tempo zu lernen. Ich kann lernen, wenn ich Zeit und Nerven dazu habe.“

Jennifer J.

Lernender seit 2020

„Bei einem spannenden neuen Projekt konnte ich die neuen Kenntnisse und Kompetenzen aus den Kursen direkt bei der Arbeit anwenden.“

Larry W.

Lernender seit 2021

„Wenn mir Kurse zu Themen fehlen, die meine Universität nicht anbietet, ist Coursera mit die beste Alternative.“

Chaitanya A.

„Man lernt nicht nur, um bei der Arbeit besser zu werden. Es geht noch um viel mehr. Bei Coursera kann ich ohne Grenzen lernen.“

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Häufig gestellte Fragen

This specialization is ideal for beginners, students, developers, programmers, software professionals, DevOps professionals, and aspiring AI developers looking to build practical skills with AI-powered developer tools.

No prerequisites are required. This is a beginner-level program designed to help learners build foundational Generative AI and AI-assisted development skills.

You'll learn GitHub Copilot, Amazon Q Developer, Windsurf, Cursor, Python, JavaScript, prompt engineering, software testing, Docker, Terraform, Infrastructure as Code, CI/CD automation, and infrastructure monitoring.