GenAI-Assisted Development and Code Quality

This course is part of GenAI for Software Developers Specialization

Instructors: Kasie Pardi

Access provided by IEM UEM Group

5 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

5 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Describe how to use generative AI tools and platforms to streamline software development
Evaluate the effectiveness of AI-integrated workflows in improving software development efficiency, accuracy, and maintainability
Develop a simple full-stack application using generative AI tools
Design complex, multi-step AI prompts to solve development challenges

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

18 assignments¹

AI Graded see disclaimer

Taught in English

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Build your subject-matter expertise

This course is part of the GenAI for Software Developers Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 5 modules in this course

This course teaches developers how to use generative AI tools to enhance software workflows, optimize code quality, and streamline debugging and testing processes. Building on foundational coding and AI concepts, you'll learn to use generative AI as both a troubleshooting aid and a quality assurance assistant. The course emphasizes real-world applications, guiding you through tasks such as test case generation, debugging, code translation, and refactoring using generative AI tools. You'll gain insights into AI-assisted testing, debugging, and code migration while maintaining industry-standard quality and security benchmarks. By the end of the course, you’ll be equipped to apply AI-powered solutions to optimize your development processes and enhance code quality.

This module introduces the fundamental principles of code quality and the role of AI in maintaining and improving codebases. You will explore techniques for identifying and resolving code smells, addressing technical debt, and utilizing AI tools to refactor and optimize code for enhanced maintainability and performance. By the end of this module, you will be equipped with the knowledge and skills to effectively apply these concepts in real-world scenarios.

What's included

7 videos3 readings4 assignments6 plugins

7 videos Total 26 minutes

Welcome to AI-Assisted Code Quality and Development 3 minutes
Introduction to AI in Software Architecture 5 minutes
Using AI Tools for Software Design and Architecture 4 minutes
AI for Full-Stack Code Generation 4 minutes
AI Generating Code Across Application Layers 4 minutes
How AI Automates Development Tasks 4 minutes
Automating a Repetitive Task with AI 3 minutes

3 readings Total 13 minutes

Course Overview 5 minutes
How to Make the Most of This Course 5 minutes
Module Summary: Designing and Developing Code with AI 3 minutes

4 assignments Total 52 minutes

Graded Quiz: Designing and Developing Code with AI 24 minutes
Practice Quiz: AI for Software Architecture & Design Decisions 10 minutes
Practice Quiz: AI-Powered Code Generation and Scaffolding 10 minutes
Practice Quiz: AI for Automating Repetitive Coding Tasks 8 minutes

6 plugins Total 56 minutes

Reading: Helpful Tools and Resources 5 minutes
Reading: Best Practices for AI-Assisted System Design 2 minutes
Reading: Application Layers and AI-Generated Code 6 minutes
Reading: Best Practices for AI-Assisted Full-Stack Development 7 minutes
Reading: Best Practices for AI-Driven Code Automation 6 minutes
Lab: Use AI to Add Key-Value Pairs to Repeated JSON Objects 30 minutes

This module focuses on how AI tools assist developers in debugging and resolving complex software issues. You will explore the capabilities of AI in identifying root causes, optimizing code for better performance, and addressing challenges in software systems. Through practical exercises and labs, you will gain hands-on experience in using AI tools to streamline problem-solving processes and enhance debugging workflows.

What's included

7 videos1 reading5 assignments1 discussion prompt8 plugins

7 videos Total 36 minutes

Introduction to Using AI to Assist with Debugging and Problem Solving 5 minutes
How AI Tools Detect and Address Bugs 5 minutes
AI Techniques for Root Cause Analysis 5 minutes
Strategies for Using Generative AI to Enable Effective Root Cause Analysis 6 minutes
Techniques for Using Generative AI to Solve Complex Development Issues 5 minutes
What Is Code Maintainability? 5 minutes
How to Use Generative AI to Reduce Technical Debt and Enhance Code Structure 5 minutes

1 reading Total 4 minutes

Module Summary: Debugging and Problem-Solving with AI 4 minutes

5 assignments Total 56 minutes

Graded Quiz: Debugging and Problem-Solving with AI 18 minutes
Practice Quiz: Fundamentals of AI-Assisted Debugging and Problem-Solving 8 minutes
Practice Quiz: Root Cause Analysis with AI Tools 10 minutes
Practice Quiz: AI for Complex Problem-Solving in Development 10 minutes
Practice Quiz: AI for Code Maintainability 10 minutes

1 discussion prompt Total 10 minutes

Reflect on How AI Tools Can Streamline Debugging and Enhance Problem-Solving in Your Development Workflows 10 minutes

8 plugins Total 116 minutes

Reading: AI-Driven Strategies for Improving Code Efficiency 6 minutes
Reading: Common Root Cause Issues in Software Development 6 minutes
Lab: Use Generative AI to Analyze the Root Cause of a Software Issue 30 minutes
Reading: Using Generative AI to help Solve Complex Development Challenges 5 minutes
Reading: Case Study with Examples for Debugging Performance, Scalability, and Architectural Issues 4 minutes
Lab: Using AI to Propose Solutions for a Complex Development Issue 30 minutes
Reading: Using AI to Refactor Legacy Codebases 5 minutes
Lab: Using Generative AI to Enhance the Structure of a Python File 30 minutes

This module explores how AI tools transform the software testing process, making it more efficient and comprehensive. You will discover how AI automates test case generation, enhance test coverage, validate workflows, and improve the overall reliability of software testing practices. Through hands-on exercises and labs, you will develop the skills to integrate AI tools into your testing workflows for better results and faster iterations.

What's included

4 videos1 reading4 assignments8 plugins

4 videos Total 20 minutes

What Is AI-Powered Testing? 4 minutes
How to Use Generative AI to Generate Test Cases 6 minutes
Step by Step Process for Using Generative AI Tools in Testing 5 minutes
Using Generative AI to Analyze Test Results and Identify Patterns 5 minutes

1 reading Total 4 minutes

Module Summary: Testing and Refactoring with AI 4 minutes

4 assignments Total 42 minutes

Graded Quiz: Testing and Refactoring with AI 14 minutes
Practice Quiz: Introduction to AI-Powered Testing 10 minutes
Practice Quiz: Automating Test Case Generation with AI 8 minutes
Practice Quiz: AI Tools for Test Analysis and Quality Assurance 10 minutes

8 plugins Total 88 minutes

Reading: Benefits of Using AI in Software Testing 4 minutes
Reading: Key Use Cases for AI in Testing Workflows 5 minutes
Reading: Case Study with Examples on Using Generative AI to Help With Common Challenges with Code Quality 5 minutes
Reading: Best Practices when Using Generative AI to Create Automated Test Cases 4 minutes
Reading: Techniques for Using Generative AI When Measuring and Enhancing Test Coverage 5 minutes
Lab: Using Generative AI to Generate Test Cases 30 minutes
Reading: How AI Helps Identify Gaps in Test Coverage and Suggests Improvements 5 minutes
Lab: Use an AI Tool to Analyze Test Coverage Reports and Generate Missing Test Cases 30 minutes

This module focuses on how AI tools assist developers in translating code across programming languages and migrating legacy systems to modern architectures. You will explore AI-driven techniques for multi-language projects, addressing compatibility issues, and optimizing migration workflows. Through practical exercises and labs, you will gain hands-on experience using AI tools to streamline and enhance code translation and migration process.

What's included

5 videos1 reading4 assignments7 plugins

5 videos Total 27 minutes

Introduction to AI-Assisted Code Translation and Migration 6 minutes
Using Generative AI Tools to Translate Code Between Languages 5 minutes
Using Generative AI to Identify Compatibility and Dependency Between Code Languages 6 minutes
AI Techniques for Resolving Dependency Conflicts 4 minutes
Using Generative AI to Support Legacy Code Modernization 6 minutes

1 reading Total 4 minutes

Module Summary: Translating and Migrating Code with AI 4 minutes

4 assignments Total 52 minutes

Graded Quiz: Translating and Migrating Code with AI 24 minutes
Practice Quiz: AI-Driven Code Translation 8 minutes
Practice Quiz: Managing Compatibility and Dependency Issues 10 minutes
Practice Quiz: Migrating Legacy Systems with AI 10 minutes

7 plugins Total 86 minutes

Reading: Benefits and Challenges of AI-Powered Code Translation 5 minutes
Reading: Best Practices for Large-Scale Codebase Translations with AI 5 minutes
Lab: Using Generative AI to Translate JavaScript to Python 30 minutes
Reading: Common Multi-Language Project Issues and AI Solutions 6 minutes
Lab: Use AI to Identify Compatibility and Dependency Challenges 30 minutes
Reading: Strategies for Migrating Legacy Systems Using Generative AI 4 minutes
Reading: Case Study with Examples of a Company Overcoming Challenges in Legacy System Migration by Using Generative AI 6 minutes

In this module, you will apply the knowledge and skills gained throughout the course to complete a final project that simulates real-world challenges. You will use AI tools to design and implement solutions for complex development scenarios, demonstrating their mastery of course concepts. The module concludes with a final assessment and reflection on how to integrate AI into future projects and workflows effectively.