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GenAI-Assisted Development and Code Quality
Course
GenAI-Assisted Development and Code Quality
Learn to use generative AI to improve your software development process. Master how to apply AI tools for debugging, testing, refactoring, and code translation.
Flexible Schedule
Intermediate Level
Mentor Support
Estimated Time
3-4 hours/week
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, youll be equipped to apply AI-powered solutions to optimize your development processes and enhance code quality.
This course comprises five purposely designed modules that take you on a carefully defined learning path.
It is a self-paced course, which means it is not run to a fixed schedule with regard to completing modules or submitting assignments. To give you an idea of how long the course takes to complete, it is anticipated that if you work 3-4 hours per week, you will complete the course in 5 weeks. However, as long as the course is completed before the end date, you can work at your own pace.
The materials for each module will become available when you start the particular module. Methods of learning and assessment will include videos, reading material, online exams questions, and a final peer review assignment.
Once you have successfully completed the course, you will earn your Certificate of Completion.
By the end of this course, you will be able to:
- Edit code and manage version control effectively.
- Design and develop robust software architecture.
- Manage development workflows efficiently.
- Program confidently in Python and JavaScript.
- Design and implement software applications.
- Software developers/engineers with 2+ years experience.
- DevOps/QA engineers looking to improve testing, debugging, and refactoring.
- Anyone interested in AI-driven prompt engineering for development.
- At least 2 years of software development experience
Course Outline
Video: Welcome to AI-Assisted Code Quality and Development (3:27)
Reading: Course Overview
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Reading: How to Make the Most of This Course
Reading: Helpful Tools and Resources
Reading: Grading Scheme
Reading: Module Introduction and Learning Objectives
Video: Introduction to AI in Software Architecture (4:39)
Video: Using AI Tools for Software Design and Architecture (4:10)
Reading: Best Practices for AI-Assisted System Design
Video: AI for Full-Stack Code Generation (3:32)
Reading: Application Layers and AI-Generated Code
Video: AI Generating Code Across Application Layers (3:31)
Reading: Best Practices for AI-Assisted Full-Stack Development
Video: How AI Automates Development Tasks (3:50)
Video: Automating a Repetitive Task with AI (3:06)
Reading: Best Practices for AI-Driven Code Automation
Lab: Use AI to Add Key-Value Pairs to Repeated JSON Objects
Practice Quiz: Designing and Developing Code with AI
Reading: Module Summary: Designing and Developing Code with AI
Graded Quiz: Designing and Developing Code with AI
Module Introduction and Learning Objectives
Video: Introduction to using AI to assist with Debugging and Problem Solving (5:20)
Video: How AI Tools Detect and Address Bugs (4:55)
Reading: AI-Driven Strategies for Improving Code Efficiency
Video: AI Techniques for Root Cause Analysis (4:37)
Reading: Common Root Cause Issues in Software Development
Video: Strategies for Using Generative AI to Enable Effective Root Cause Analysis (6:18)
Lab: Use Generative AI to Analyze the Root Cause of a Software Issue
Reading: Using Generative AI to help Solve Complex Development Challenges
Video: Techniques for using Generative AI to solve Complex Development Issues (4:40)
Reading: Case Study with Examples for Debugging Performance, Scalability, and Architectural Issues
Lab: Using AI to Propose Solutions for a Complex Development Issue
Video: What Is Code Maintainability? (5:18)
Video: How to Use Generative AI to Reduce Technical Debt and Enhance Code Structure (5:17)
Reading: Using AI to Refactor Legacy Codebases
Lab: Using Generative AI to Enhance the Structure of a Python File
Practice Quiz: Debugging and Problem Solving with AI
Reading: Module Summary: Debugging and Problem-Solving with AI
Graded Quiz: Debugging and Problem-Solving with AI
Module Introduction and Learning Objectives
Video: What Is AI-Powered Testing? (4:25)
Reading: Benefits of Using AI in Software Testing
Reading: Key Use Cases for AI in Testing Workflows
Reading: Case Study with Examples on Using Generative AI to Help With Common Challenges with Code Quality
Video: How to use Generative AI to Generate Test Cases (5:33)
Reading: Best Practices when Using Generative AI to Create Automated Test Cases
Video: Step by Step Process for Using Generative AI Tools in Testing (5:01)
Reading: Techniques for Using Generative AI When Measuring and Enhancing Test Coverage
Lab: Using Generative AI to Generate Test Cases
Video: Using Generative AI to Analyze Test Results and Identify Patterns (4:40)
Reading: How AI Helps Identify Gaps in Test Coverage and Suggests Improvements
Lab: Use an AI Tool to Analyze Test Coverage Reports and Generate Missing Test Cases
Practice Quiz: Testing and Refactoring with AI
Reading: Module Summary: Testing and Refactoring with AI
Graded Quiz: Testing and Refactoring with AI
Module Introduction and Learning Objectives
Video: Introduction to AI-Assisted Code Translation and Migration (5:55)
Reading: Benefits and Challenges of AI-Powered Code Translation
Video: Using Generative AI Tools to Translate Code Between Languages (5:14)
Reading: Best Practices for Large-Scale Codebase Translations with AI
Lab: Using Generative AI to Translate JavaScript to Python
Video: Using Generative AI to Identify Compatibility and Dependency Between Code Languages (5:31)
Reading: Common Multi-Language Project Issues and AI Solutions
Video: AI Techniques for Resolving Dependency Conflicts (4:28)
Lab: Use AI to Identify Compatibility and Dependency Challenges
Video: Using Generative AI to Support Legacy Code Modernization (6:06)
Reading: Strategies for Migrating Legacy Systems Using Generative AI
Reading: Case Study with Examples of a Company Overcoming Challenges in Legacy System Migration by Using Generative AI
Practice Quiz: Translating and Migrating Code with AI
Reading: Module Summary: Translating and Migrating Code with AI
Graded Quiz: Translating and Migrating Code with AI
Module Introduction and Learning Objectives
Final Project: Using Generative AI Tools to Debug and Fix Software Bugs
Final Project: Submission and Evaluation
Video: Course Summary (4:06)
Glossary: GenAI-Assisted Development and Code Quality
Graded Quiz: GenAI-Assisted Development and Code Quality
Reading: Congratulations and Next Steps
Reading: Thanks from the Course Team
Why Learn with SkillUp Online?
We believe every learner is an individual and every course is an opportunity to build job-ready skills. Through our human-centered approach to learning, we will empower you to fulfil your professional and personal goals and enjoy career success.
Reskilling into tech? We’ll support you.
Upskilling for promotion? We’ll help you.
Cross-skilling for your career? We’ll guide you.
Personalized Mentoring & Support
1-on-1 mentoring, live classes, webinars, weekly feedback, peer discussion, and much more.
Practical Experience
Hands-on labs and projects tackling real-world challenges. Great for your resumé and LinkedIn profile.
Best-in-Class Course Content
Designed by the industry for the industry so you can build job-ready skills.
Job-Ready Skills Focus
Competency building and global certifications employers are actively looking for.
FAQs
This course shows how generative AI tools enhance code accuracy, streamline workflows, and support consistent quality checks across development tasks.
You will learn practical methods for using AI-driven code optimization, intelligent coding assistants, and automated review techniques to refine structure, logic, and maintainability.
The course demonstrates how GenAI developers can support code refactoring, test creation, performance tuning, and the detection of structural issues early in the workflow.
Youll explore how to integrate AI into planning, coding, testing, and documentation, creating seamless development pipelines aligned with modern engineering practices.
AI tools are applied to analyze system patterns, recommend architectural components, and support structured decision-making during application design.
You will practice using AI-powered code generation techniques and translation workflows to migrate codebases, optimize logic, and modernize applications.
Youll build capabilities in prompt engineering, unit testing, code review, debugging with AI, multi-step prompt design, and full-stack development supported by generative AI.
No prior AI background is required. The course introduces essential concepts before moving into advanced GenAI for developers scenarios.
Yes, the course includes a Certificate of Completion upon successful completion of the course, validating your newly acquired skills.
You will learn to build AI-assisted applications, generate test cases automatically, apply AI software testing courses methods, and streamline debugging with AI for real-world development.
GenAI supports developers by reducing manual effort, providing intelligent suggestions, improving testing speed, and enhancing the accuracy of development tasks.
Yes, through AI courses for software testing youll see how generative AI helps generate tests, evaluate code behavior, and support automated validation.
This course includes testing, but it goes further by covering full-stack development, architectural analysis, multi-step reasoning, and integrated GenAI for developers workflows.
An AI coding course online strengthens technical versatility, enabling you to adopt AI-driven development practices that improve productivity and code quality in modern engineering roles.
Type of certificate
IBM Certificate
About this course
05 Modules
05 Skills
Includes
Discussion space
08 Hands-on labs
04 Practice quizzes
04 Graded quizzes
01 Final project
01 Final exam
Create
Key-Value Pairs to Repeated JSON Objects
Exercises to explore
Analyze the Root Cause of a Software Issue
Propose Solutions for a Complex Development Issue
Enhance the Structure of a Python File
Generate Test Cases
Analyze Test Coverage Reports and Generate Missing Test Cases
Translate JavaScript to Python
This course has been created by
Paul Pardi
Subject Matter Expert - Technical content
Kasie Pardi
Subject Matter Expert - Technical content
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