LLMs for Code Understanding, Refactoring, and Documentation Training Course
The course on LLMs for Code Comprehension, Refactoring, and Documentation is a technical program dedicated to leveraging large language models (LLMs) to enhance code quality, minimize technical debt, and automate documentation processes across software engineering teams.
This instructor-led, live training session, available in online or onsite formats, targets intermediate to advanced software professionals seeking to utilize LLMs, such as GPT, to more effectively analyze, refactor, and document complex or legacy codebases.
Upon completion of this training, participants will be equipped to:
- Employ LLMs to clarify code, dependencies, and logic within unfamiliar repositories.
- Detect and refactor anti-patterns to enhance code readability.
- Automate the generation and maintenance of inline comments, README files, and API documentation.
- Integrate LLM-driven insights into existing CI/CD pipelines and code review workflows.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical practice.
- Hands-on implementation within a live-lab environment.
Customization Options
- To request tailored training 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
- Analyzing 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 for suggesting 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 in 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 demos
Ethics, Quality Assurance, and Review
- Validating AI-generated changes and avoiding hallucinations
- Peer review best practices 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
- 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
Upcoming Courses
Related Courses
Advanced GitHub Copilot & AI for Projects and Infrastructure
14 HoursGitHub Copilot is an AI-driven code completion tool designed to accelerate development processes while enhancing both quality and productivity. When combined with Artificial Intelligence applications in project management, infrastructure, and software development, managers can utilize AI to optimize resource distribution, streamline workflows, and improve decision-making.
This instructor-led live training (available online or onsite) targets advanced-level managers who wish to deepen their understanding of GitHub Copilot and explore practical AI applications within corporate settings, with examples relevant to large-scale projects and industries such as oil and gas.
Upon completion 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 optimize project management, infrastructure, and software acquisition.
- Implement AI-based strategies to improve planning, estimation, and time optimization.
- Recognize practical AI applications in industry-specific scenarios such as oil and gas.
Course Format
- Interactive lectures and discussions.
- Hands-on exercises and case studies.
- Live-lab demonstrations of AI tools and Copilot workflows.
Course Customization Options
- To request a customized 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 allows engineers to extend, fine-tune, and customize its coding intelligence for specialized use cases and enterprise workflows.
This instructor-led, live training (online or onsite) is aimed at advanced-level developers and AI engineers who wish to design tailored prompt systems, fine-tune model behavior, and build custom extensions for internal development automation.
By the conclusion of this training, participants will be able to:
- Design and test advanced prompt templates for precise AI behavior.
- Connect Cursor to internal APIs and knowledge bases for context-aware code generation.
- Develop fine-tuned or domain-adapted AI models for specialized tasks.
- Build and deploy custom tools or adapters that extend Cursor’s functionality securely.
Format of the Course
- Technical presentations and guided demonstrations.
- Hands-on development and prompt optimization labs.
- Practical projects integrating Cursor with real-world enterprise systems.
Course Customization Options
- This course can be customized to align with specific internal architectures, AI frameworks, or security compliance requirements.
Advanced GitHub Copilot
14 HoursThis instructor-led, live training in Romania (offered online or on-site) targets advanced-level attendees who want to customize GitHub Copilot for team projects, leverage its sophisticated features, and integrate it into CI/CD pipelines to improve collaboration and productivity.
By the conclusion of this training, participants will be able to:
- Customize GitHub Copilot to align with specific project requirements and team workflows.
- Apply Copilot’s advanced capabilities to address complex coding tasks.
- Integrate GitHub Copilot into CI/CD pipelines and collaborative environments.
- Optimize team collaboration using AI-enabled tools.
- Effectively manage and troubleshoot Copilot settings and user permissions.
GitHub Copilot: Advanced Agent Mode
21 HoursThis instructor-led, live training in Romania (online or onsite) is designed for developers who want 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-driven coding assistant designed to automate development tasks, including DevOps operations such as writing YAML configurations, GitHub Actions, and deployment scripts.
This instructor-led, live training (available online or onsite) targets beginner 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 Customization Options
- To request a customized training for this course, please contact us to arrange.
AI-Assisted Development & Coding with Cursor
21 HoursThis guided, live training session (available online or in-person) is designed for mid-level software developers looking to enhance their productivity and improve code quality through AI-assisted coding with Cursor.
Upon completion of this course, participants will be able to:
- Set up and configure Cursor for AI-enhanced software development.
- Seamlessly integrate Cursor with Git repositories and existing development workflows.
- Utilize natural language commands to create, debug, and optimize code.
- Apply AI tools for refactoring, documentation, and testing processes.
Cursor for Data & ML Engineering: Notebooks, Pipelines & Model Ops
14 HoursCursor is an AI-enhanced development environment designed to boost productivity and reliability in data and machine learning workflows. It achieves this through intelligent code generation, context-aware suggestions, and streamlined documentation.
This instructor-led live training, available online or onsite, targets intermediate-level data and ML professionals seeking to integrate Cursor into their daily workflows. The goal is to enable faster prototyping, scalable pipeline development, and improved model operations.
Upon completing this training, participants will be able to:
- Utilize 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.
- Improve reproducibility, collaboration, and operational consistency within ML workflows.
Course Format
- Interactive lectures and demonstrations.
- Practical, hands-on exercises in live coding environments.
- Case studies integrating Cursor with ML pipelines and model ops tools.
Customization Options
- This training can be customized to specific frameworks such as TensorFlow, PyTorch, or scikit-learn, or to align with organizational MLOps platforms.
Cursor Fundamentals: Accelerating Developer Productivity
14 HoursCursor is an AI-driven code editor built to boost developer efficiency by providing intelligent code completions, contextual edits, and adaptive support.
This instructor-led live training, available online or on-site, targets beginner-level developers and engineering teams aiming to streamline their coding workflows and safely utilize AI suggestions to enhance efficiency.
Upon completing 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.
Course Format
- Interactive lecture and discussion.
- Hands-on demonstrations and guided exercises.
- Real-world coding challenges and lab practice using Cursor.
Course Customization 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 intelligent, AI-driven development environment designed to boost team collaboration, automate code reviews, and integrate effortlessly into contemporary CI/CD workflows.
This instructor-led live training, available either online or onsite, targets intermediate-level technical professionals seeking to incorporate Cursor into their team workflows to improve collaboration, streamline code reviews, and uphold quality standards across automated pipelines.
Upon completion of this training, participants will be able to:
- Configure and manage team environments within Cursor for collaborative development.
- Utilize AI tools to automate code reviews, generate pull requests, and validate merges.
- Enforce code governance, review policies, and security guidelines using Cursor’s features.
- Connect Cursor with CI/CD systems to ensure continuous delivery and consistent quality.
Course Format
- Instructor-led presentations coupled with team-based discussions.
- Practical labs based on real-world team collaboration scenarios.
- Live integration exercises involving CI/CD and version control tools.
Customization Options
- The curriculum can be tailored to specific CI/CD platforms, repository tools, or enterprise security needs.
GitHub Copilot for Developers
14 HoursThis instructor-led, live training in Romania (online or onsite) targets beginner to intermediate-level developers seeking to learn how to effectively harness the capabilities of GitHub Copilot within modern development workflows.
GitHub Copilot in Team Environments: Collaboration Best Practices
14 HoursThis instructor-led, live training in Romania (online or onsite) is designed for intermediate to advanced participants who wish to optimize 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.
- Utilize Copilot to enhance collaborative coding practices.
- Optimize 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 Romania (online or onsite) is tailored for beginner-level developers aiming to boost their coding efficiency with Tabnine.
By the end of this session, participants will be able to:
- Install and configure Tabnine in their preferred IDE.
- Utilize Tabnine's autocomplete features to accelerate coding.
- Customize 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 Romania (online or onsite) is aimed at advanced-level developers and team leads who wish to master advanced features of Tabnine.
By the end of this training, participants will be able to:
- Implement Tabnine in complex software projects.
- Customize 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 Romania (online or onsite) is designed for developers from novice to expert levels who wish to utilize AI for code generation with Tabnine.
By the end of this training, participants will be able to:
- Understand the basics of AI-powered code generation.
- Install and configure Tabnine in their development environment.
- Utilize Tabnine for efficient code completion and error correction.
- Create and train custom AI models with Tabnine for specialized tasks.
Tabnine for Python Developers
14 HoursThis instructor-led, live training in Romania (online or onsite) is designed for intermediate-level Python developers and data scientists who want to increase their productivity with the assistance of Tabnine.
By the end of this training, participants will be able to:
- Install and configure Tabnine in their Python development environment.
- Utilize Tabnine's autocomplete features to write Python code more efficiently.
- Customize Tabnine's behavior to suit their coding style and project needs.
- Understand how Tabnine's AI model specifically works with Python code.