Build maintainable, high-quality software with clean code, refactoring, and responsible AI-assisted engineering.
Growing code complexity, technical debt, and AI-generated code can make software harder to maintain. This immersive 3-day training helps engineering teams improve code quality, refactor safely, design flexible systems, and adopt sustainable engineering practices with AI.
- Why get trained: Learn clean coding, refactoring, design principles, technical debt management, code reviews, and responsible AI-assisted engineering.
- Why it matters: Reduce technical debt, improve maintainability, increase code quality, and build software that can evolve reliably over time.
- Who should attend: Software Engineers, Full Stack Developers, Backend/Frontend Developers, Technical Leads, Engineering Managers, Architects, and Quality Engineers.
Gain hands-on experience through code reviews, refactoring exercises, real-world engineering scenarios, AI-assisted workflows, and practical workshops. HRD Corp Claimable.
Overview
Modern software systems are becoming increasingly difficult to maintain due to growing code complexity, rapid delivery expectations, legacy constraints, inconsistent engineering practices, and the introduction of AI-generated code into production environments.
Sustainable software engineering requires a strong focus on technical debt management, maintainability, design evolution, engineering craftsmanship, quality systems, and responsible AI-assisted development workflows.
This immersive 3-day training helps engineering teams build maintainable, evolvable, and sustainable software systems through practical, hands-on learning. Participants will learn techniques for improving code quality, reducing technical debt, refactoring safely, designing flexible systems, and integrating AI-assisted engineering practices responsibly.
The training emphasizes real-world engineering through code reading, refactoring, design improvement, engineering decision-making, and practical development workflows.
Skills Covered
- Understand code as long-term organizational liability
- Explain technical debt economics and maintainability trade-offs
- Evaluate software quality beyond “working code”
- Write readable, maintainable, and extensible code
- Apply refactoring techniques safely
- Improve functions, class design, and modularity
- Reduce complexity and improve testability
- Apply design principles
- Design systems for flexibility and evolvability
- Use AI responsibly for refactoring, code review, and technical debt analysis
- Understand risks of AI-generated code
- Implement sustainable engineering workflows
- Apply quality gates and code review practices
- Improve visibility of technical debt and code quality metrics
Prerequisites
No experienced needed. The training introduces AI-assisted engineering concepts and demonstrates how AI can be used responsibly within software development workflows.
Target Audience
- Software Engineers
- Full Stack Developers
- Backend / Frontend Developers
- Technical Leads
- Engineering Managers
- Architects
- Quality Engineers
Exam & Certification
Complete the Clean Code Engineering in the AI Era Training and receive your Clean Code Engineering in the AI Era Training Certificate of Completion after successfully completing the 3-day program. This validates your skills in writing maintainable code, managing technical debt, applying clean code and refactoring practices, improving software design, and responsibly using AI-assisted engineering workflows.
Training & Certification Guide
Why train with Trainocate
Speak to a Training Consultant
All courses are HRD Claimable.
Get in touch with our team via the form or WhatsApp us on +6011-5119 6631
