LLMs for Code Understanding, Refactoring, and Documentation Training Course
LLMs for Code Understanding, Refactoring, and Documentation is a technical course focused on applying large language models (LLMs) to enhance code quality, reduce technical debt, and automate documentation tasks across software teams.
This instructor-led, live training (delivered either online or on-site) is designed for intermediate to advanced-level software professionals who wish to leverage LLMs, such as GPT, to more effectively analyse, refactor, and document complex or legacy codebases.
By the end of this training, participants will be able to:
- Use LLMs to explain code, dependencies, and logic in unfamiliar repositories.
- Identify and refactor anti-patterns while improving code readability.
- Automatically generate and maintain inline comments, README files, and API documentation.
- Integrate LLM-driven insights into existing CI/CD and review workflows.
Course Format
- Interactive lectures and discussions.
- Abundant exercises and practical activities.
- Hands-on implementation within a live-lab environment.
Course Customisation Options
- To request a customised training session for this course, please contact us to make arrangements.
Course Outline
Understanding Code with LLMs
- Prompting strategies for code explanation and walkthroughs
- Working with unfamiliar codebases and projects
- Analysing control flow, dependencies, and architecture
Refactoring Code for Maintainability
- Identifying code smells, dead code, and anti-patterns
- Restructuring functions and modules for clarity
- Using LLMs to suggest naming conventions and design improvements
Improving Performance and Reliability
- Detecting inefficiencies and security risks with AI assistance
- Suggesting more efficient algorithms or libraries
- Refactoring I/O operations, database queries, and API calls
Automating Code Documentation
- Generating function/method-level comments and summaries
- Writing and updating README files from codebases
- Creating Swagger/OpenAPI docs with LLM support
Integration with Toolchains
- Using VS Code extensions and Copilot Labs for documentation
- Incorporating GPT or Claude into Git pre-commit hooks
- CI pipeline integration for documentation and linting
Working with Legacy and Multi-Language Codebases
- Reverse-engineering older or undocumented systems
- Cross-language refactoring (e.g., from Python to TypeScript)
- Case studies and pair-AI programming demonstrations
Ethics, Quality Assurance, and Review
- Validating AI-generated changes and avoiding hallucinations
- Best practices for peer review when using LLMs
- Ensuring reproducibility and compliance with coding standards
Summary and Next Steps
Requirements
- Experience with programming languages such as Python, Java, or JavaScript
- Familiarity with software architecture and code review processes
- A basic understanding of how large language models function
Audience
- Backend engineers
- DevOps teams
- Senior developers and tech leads
Open Training Courses require 5+ participants.
LLMs for Code Understanding, Refactoring, and Documentation Training Course - Booking
LLMs for Code Understanding, Refactoring, and Documentation Training Course - Enquiry
LLMs for Code Understanding, Refactoring, and Documentation - Consultancy Enquiry
Testimonials (1)
That i gained a knowledge regarding streamlit library from python and for sure i'll try to use it to improve applications in my team which are made in R shiny
Michal Maj - XL Catlin Services SE (AXA XL)
Course - GitHub Copilot for Developers
Provisional Upcoming Courses (Require 5+ participants)
Related Courses
Advanced GitHub Copilot & AI for Projects and Infrastructure
14 HoursGitHub Copilot is an AI-powered code completion tool that helps accelerate development while improving quality and productivity. Combined with Artificial Intelligence applications in projects, infrastructure, and software, managers can leverage AI to optimise resource allocation, streamline workflows, and enhance decision-making.
This instructor-led, live training (online or onsite) is aimed at advanced-level managers who wish to deepen their knowledge of GitHub Copilot while also exploring practical AI applications in corporate environments, with examples relevant to large-scale projects and industries such as oil and gas.
By the end of this training, participants will be able to:
- Apply advanced Copilot functionalities in large-scale corporate projects.
- Integrate Copilot into multidisciplinary workflows for maximum efficiency.
- Leverage AI tools to optimise project management, infrastructure, and software acquisition.
- Implement AI-based strategies to improve planning, estimation, and time optimisation.
- Recognise practical AI applications in industry-specific scenarios such as oil and gas.
Format of the Course
- Interactive lecture and discussion.
- Hands-on exercises and case studies.
- Live-lab demonstrations of AI tools and Copilot workflows.
Course Customisation Options
- To request a customised training for this course, please contact us to arrange.
Advanced Cursor: Prompt Engineering, Fine-Tuning & Custom Tooling
14 HoursCursor is an advanced AI-powered development environment that enables engineers to extend, fine-tune, and customise its coding intelligence for specialised use cases and enterprise workflows.
This instructor-led, live training (delivered online or on-site) is designed for advanced-level developers and AI engineers who aim to design tailored prompt systems, fine-tune model behaviour, and build custom extensions to automate internal development processes.
By the end of this training, participants will be able to:
- Design and test advanced prompt templates to achieve precise AI behaviour.
- Connect Cursor to internal APIs and knowledge bases for context-aware code generation.
- Develop fine-tuned or domain-adapted AI models for specialised tasks.
- Build and deploy custom tools or adapters that securely extend Cursor’s functionality.
Course Format
- Technical presentations and guided demonstrations.
- Hands-on development and prompt optimisation labs.
- Practical projects integrating Cursor with real-world enterprise systems.
Course Customisation Options
- This course can be customised to align with specific internal architectures, AI frameworks, or security compliance requirements.
Advanced GitHub Copilot
14 HoursThis instructor-led, live training in New Zealand (online or onsite) is aimed at advanced-level participants who wish to customise GitHub Copilot for team projects, utilise its advanced features, and integrate it seamlessly into CI/CD pipelines for enhanced collaboration and productivity.
By the end of this training, participants will be able to:
- Customise GitHub Copilot for specific project needs and team workflows.
- Leverage advanced features of Copilot for complex coding tasks.
- Integrate GitHub Copilot into CI/CD pipelines and collaborative environments.
- Optimise team collaboration using AI-powered tools.
- Manage and troubleshoot Copilot settings and permissions effectively.
GitHub Copilot: Advanced Agent Mode
21 HoursThis instructor-led, live training held in New Zealand (online or onsite) is aimed at developers who wish to use GitHub Copilot Agent Mode to autonomously build features, run tests, and manage larger coding tasks.
By the end of this training, participants will be able to activate Agent Mode, plan and iterate within the agent loop, execute terminal commands, and implement enterprise governance.
GitHub Copilot for DevOps Automation and Productivity
14 HoursGitHub Copilot is an AI-powered coding assistant that helps automate development tasks, including DevOps operations such as writing YAML configurations, GitHub Actions, and deployment scripts.
This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level professionals who wish to use GitHub Copilot to streamline DevOps tasks, improve automation, and boost productivity.
By the end of this training, participants will be able to:
- Use GitHub Copilot to assist with shell scripting, configuration, and CI/CD pipelines.
- Leverage AI code completion in YAML files and GitHub Actions.
- Accelerate testing, deployment, and automation workflows.
- Apply Copilot responsibly with an understanding of AI limitations and best practices.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customisation Options
- To request a customised training for this course, please contact us to arrange.
AI-Assisted Development & Coding with Cursor
21 HoursThis instructor-led, live training (online or on-site) is designed for intermediate-level software developers who want to boost productivity and code quality through AI-assisted coding with Cursor.
By the end of this training, participants will be able to:
- Install and configure Cursor for AI-assisted software development.
- Integrate Cursor with Git repositories and development workflows.
- Use natural language to generate, debug, and optimise code.
- Leverage AI capabilities for refactoring, documentation, and testing.
Cursor for Data & ML Engineering: Notebooks, Pipelines & Model Ops
14 HoursCursor is an AI-powered development environment that boosts productivity and reliability across data and machine learning workflows through intelligent code generation, context-aware suggestions, and streamlined documentation.
This instructor-led, live training (available online or on-site) is designed for intermediate-level data and ML professionals looking to integrate Cursor into their daily workflows for faster prototyping, scalable pipeline development, and improved model operations.
By the end of this training, participants will be able to:
- Use Cursor to speed up notebook development and code exploration.
- Generate, refactor, and document ETL and feature engineering pipelines.
- Leverage AI-assisted code for model training, tuning, and evaluation.
- Enhance reproducibility, collaboration, and operational consistency in ML workflows.
Course Format
- Interactive lectures and live demonstrations.
- Hands-on exercises in live coding environments.
- Case studies integrating Cursor with ML pipelines and model operations tools.
Course Customisation Options
- This training can be tailored to specific frameworks such as TensorFlow, PyTorch, or scikit-learn, or to organisational MLOps platforms.
Cursor Fundamentals: Accelerating Developer Productivity
14 HoursCursor is an AI-powered code editor designed to enhance developer productivity through intelligent code completions, contextual edits, and adaptive assistance.
This instructor-led, live training (online or onsite) is aimed at beginner-level developers and engineering teams who wish to streamline their coding workflow and safely leverage AI suggestions for improved efficiency.
Upon completion of this training, participants will be able to:
- Install and configure Cursor for optimal use in development projects.
- Understand and apply AI-assisted code completion, in-editor chat, and refactoring tools.
- Evaluate, accept, or modify AI-generated code suggestions effectively and securely.
- Adopt best practices for team onboarding, collaboration, and version control integration.
Format of the Course
- Interactive lecture and discussion.
- Hands-on demonstrations and guided exercises.
- Real-world coding challenges and lab practice using Cursor.
Course Customisation Options
- This course can be tailored to specific programming languages or frameworks used by your team.
Cursor for Teams: Collaboration, Code Review & CI/CD Integration
14 HoursCursor is an AI-powered development environment that enhances team collaboration, automates code reviews, and integrates seamlessly into modern CI/CD workflows.
This instructor-led, live training (online or on-site) is aimed at intermediate-level technical professionals who wish to integrate Cursor into their team environments to improve collaboration, streamline reviews, and maintain quality across automated pipelines.
Upon completing this training, participants will be able to:
- Set up and manage team environments in Cursor for collaborative development.
- Leverage AI tools for automated code reviews, pull request generation, and merge validation.
- Implement code governance, review policies, and security guardrails using Cursor’s capabilities.
- Integrate Cursor with CI/CD systems to ensure continuous delivery and consistent quality standards.
Course Format
- Instructor-led presentations and team-based discussions.
- Hands-on labs using real-world team collaboration scenarios.
- Live integration exercises with CI/CD and version control tools.
Course Customisation Options
- The course can be adapted to specific CI/CD platforms, repository tools, or enterprise security requirements.
GitHub Copilot for Developers
14 HoursThis instructor-led, live training in New Zealand (online or on-site) is aimed at beginner to intermediate-level developers who wish to learn how to utilise the capabilities of GitHub Copilot effectively within modern development workflows.
GitHub Copilot in Team Environments: Collaboration Best Practices
14 HoursThis instructor-led, live training in New Zealand (online or onsite) is aimed at intermediate-level to advanced-level participants who wish to optimise team workflows, enhance collaborative coding practices, and effectively manage Copilot usage in multi-developer environments.
By the end of this training, participants will be able to:
- Set up GitHub Copilot for team environments.
- Utilise Copilot to enhance collaborative coding practices.
- Optimise team workflows using Copilot's features.
- Manage Copilot's integration in multi-developer projects.
- Maintain consistent code quality and standards across teams.
- Leverage advanced Copilot features for team-specific needs.
- Combine Copilot with other collaborative tools for efficiency.
Tabnine for Beginners
14 HoursThis instructor-led, live training in New Zealand (online or onsite) is aimed at beginner-level developers who wish to increase their coding efficiency with the help of Tabnine.
By the end of this training, participants will be able to:
- Install and set up Tabnine in their preferred IDE.
- Utilise Tabnine's autocomplete features to speed up coding.
- Customise Tabnine's settings for optimal assistance.
- Understand how Tabnine's AI learns from their code to provide better suggestions.
Tabnine for Advanced Developers
14 HoursThis instructor-led, live training in New Zealand (delivered online or on-site) is designed for advanced-level developers and team leads who aim to master Tabnine's advanced features.
By the conclusion of this training, participants will be able to:
- Deploy Tabnine within complex software projects.
- Customise and train Tabnine's AI models for specific use cases.
- Integrate Tabnine into team workflows and development pipelines.
- Enhance code quality and accelerate development cycles using Tabnine's insights.
Tabnine: Code Smarter with AI
21 HoursThis instructor-led, live training in New Zealand (online or on-site) is tailored for developers at all skill levels—from beginners to experts—who want to harness AI for code generation using Tabnine.
By the end of this training, participants will be able to:
- Grasp the fundamentals of AI-powered code generation.
- Install and configure Tabnine within their development environment.
- Leverage Tabnine for efficient code completion and error correction.
- Build and train custom AI models with Tabnine for specialised tasks.
Tabnine for Python Developers
14 HoursThis instructor-led, live training in New Zealand (online or on-site) is designed for intermediate-level Python developers and data scientists looking to enhance their productivity with the help of Tabnine.
By the end of this training, participants will be able to:
- Install and configure Tabnine within their Python development environment.
- Use Tabnine's autocomplete capabilities to write Python code more efficiently.
- Customise Tabnine's behaviour to align with their coding style and project requirements.
- Understand how Tabnine's AI model operates specifically with Python code.