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

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

Instructors: Professionals in the Industry

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4 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

8 hours to complete

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

8 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Explain the transformative role of Generative AI in software development.
Apply AI tools to enhance coding and testing processes.
Improve software design using AI-driven insights.
Develop innovative solutions with effective AI integration.

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There are 4 modules in this course

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, it 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 tools like GitHub Copilot, 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 applying AI across real development workflows. Designed for developers, QA engineers, DevOps professionals, and architects with basic programming knowledge, this four-hour course equips learners to confidently integrate Generative AI into software engineering while balancing innovation with responsible human oversight.

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

What's included

11 videos3 readings1 assignment1 peer review1 discussion prompt

11 videosTotal 58 minutes

Intro Video to Course 3 minutes
Module Introduction 1 minute
Overview of Code Generation Tools 5 minutes
Setting Up AI Coding Assistants 8 minutes
Prompt Patterns for Coding 7 minutes
Generating Simple Functions and Classes 6 minutes
Boilerplate and Complex Structures 7 minutes
Case Study: AI Code Generation Project 5 minutes
Code Review & Security Analysis 6 minutes
Refactoring for Maintainability 4 minutes
Testing and Debugging AI-Generated Code 5 minutes

3 readingsTotal 15 minutes

Welcome to the Course: Course Overview5 minutes
AI in Modern Software Development 5 minutes
Choosing the Right AI Tool for Your Project 5 minutes

1 assignmentTotal 20 minutes

AI-Assisted Coding Fundamentals20 minutes

1 peer reviewTotal 10 minutes

Hands-On-Learning: Integrating an AI Assistant into a Simple Project 10 minutes

1 discussion promptTotal 5 minutes

Ethical Implications & Integration Challenges5 minutes

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

What's included

10 videos1 reading1 assignment1 peer review1 discussion prompt

10 videosTotal 66 minutes

Module Introduction 1 minute
Requirements to Code Outlines 7 minutes
AI for Database Design and Queries 7 minutes
Case Study on AI in Design Phase 5 minutes
Generating API Endpoints 5 minutes
AI for Integration Development 10 minutes
Debugging APIs with AI 10 minutes
Generating Inline Code Comments 5 minutes
Creating Comprehensive Documentation 9 minutes
Automating Documentation Workflows with AI 7 minutes

1 readingTotal 5 minutes

AI Tools for Developers 5 minutes

1 assignmentTotal 20 minutes

Development Workflow Optimization with AI20 minutes

1 peer reviewTotal 10 minutes

Hands-On-Learning: Managing Complexity & Documentation Challenges 10 minutes

1 discussion promptTotal 5 minutes

Managing Complexity & Documentation Challenges5 minutes

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.

What's included

10 videos1 reading1 assignment1 peer review1 discussion prompt

10 videosTotal 57 minutes

Module Introduction 1 minute
Introduction to AI in Software Testing 4 minutes
Generating Unit, Integration, and End-to-End Tests 5 minutes
Case Study on Maximising Test Coverage 5 minutes
Writing Automated Testing Scripts with AI 7 minutes
Using AI for Bug Detection and Root Cause Analysis 6 minutes
AI for Suggesting Bug Fixes 4 minutes
AI for Performance Optimisation 8 minutes
Identifying Vulnerabilities with AI 12 minutes
How AI Anticipates Bugs and Failures Before They Happens 5 minutes

1 readingTotal 5 minutes

AI and Software Testing 5 minutes

1 assignmentTotal 20 minutes

Testing and Quality Assurance20 minutes

1 peer reviewTotal 10 minutes

Hands-On-Learning: Evolution of the QA Role & Limitations of AI 10 minutes

1 discussion promptTotal 10 minutes

Evolution of the QA Role & Limitations of AI10 minutes

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

What's included

11 videos1 reading1 assignment2 peer reviews1 discussion prompt

11 videosTotal 63 minutes

Module Introduction 1 minute
Introduction to AI for Infrastructure as Code 5 minutes
Generating Terraform and Ansible Code with AI9 minutes
Case Study on Automated Infrastructure Provisioning 6 minutes
Optimising CI/CD Scripts with GenAI 7 minutes
Analysing Build Failures with AI 6 minutes
Automated Monitoring & Alerting with AI 6 minutes
Automating Incident Response 5 minutes
Real-time Performance Analysis and Scaling Suggestions 7 minutes
Autonomous Reliability Engineering with AI 8 minutes
Course Wrap-up Video 2 minutes

1 readingTotal 5 minutes

AI in DevOps 5 minutes

1 assignmentTotal 20 minutes

DevOps and Deployment with Generative AI20 minutes

2 peer reviewsTotal 70 minutes

Hands-On-Learning: Preventing "Pipeline Hell" & Automation Risks 10 minutes
Project: Integrating AI Tools Across the Software Development Life Cycle 60 minutes

1 discussion promptTotal 10 minutes

The Future of Infrastructure with AI10 minutes

Instructors

Professionals in the Industry

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