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AI for Application Development: End-to-End AI Workflow

Starweaver via Coursera

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Details

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

4 weeks, 2 hours a week
Sessions

Self-Paced
Level

Intermediate
Subtitles

English

Found in

Overview

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Generative AI is transforming how software is designed, built, tested, and deployed, becoming an essential tool for developers, engineers, architects, and technology leaders. Rather than replacing human expertise, AI for application development enhances productivity by accelerating workflows, improving code quality, and automating repetitive tasks. This course provides a practical, end-to-end journey through the software development lifecycle, showing how AI can be integrated into coding, documentation, testing, DevOps, and deployment. Learners begin with AI-assisted coding using AI tools for app development such as GitHub Copilot, along with prompt engineering and code generation, before exploring AI-powered requirements analysis, API development, database design, and documentation. The course then covers AI-driven testing, bug detection, performance optimization, and security, followed by DevOps automation, Infrastructure as Code, CI/CD, monitoring, and incident response. Through hands-on labs, quizzes, discussions, and a capstone project, learners gain practical experience building AI apps and applying AI across real development workflows. Designed for developers, QA engineers, DevOps professionals, and architects with basic programming knowledge, this four-hour AI for application development course equips learners to confidently integrate generative AI into software engineering while balancing innovation with responsible human oversight.

Syllabus

AI-Assisted Coding Fundamentals

This inaugural module provides the foundational knowledge and practical skills for integrating Generative AI into the core process of writing and managing code.

Development Workflow Optimization with AI

This module elevates the application of Generative AI from individual coding tasks to the broader, end-to-end software development workflow.

Testing and Quality Assurance

This module is designed to address the needs of the QA engineer persona by demonstrating how Generative AI can significantly enhance the efficiency and efficacy of the testing process.

DevOps and Deployment with Generative AI

This final, capstone module integrates Generative AI into the deployment and operational pipeline, demonstrating its potential for full-stack automation.