LLMs for Code Understanding, Refactoring, and Documentation Training Course

GitHub Copilot is an AI-driven code completion assistant designed to boost development speed while enhancing code quality and overall productivity. When integrated with Artificial Intelligence applications in projects, infrastructure, and software systems, managers can harness AI to optimize resource distribution, streamline operational workflows, and strengthen decision-making processes.

This instructor-led live training, available online or onsite, targets advanced-level managers seeking to deepen their expertise in GitHub Copilot and explore practical AI applications within corporate settings. The curriculum includes examples pertinent to large-scale projects and sectors such as the oil and gas industry.

Upon completing this training, participants will be equipped to:

• Utilize advanced Copilot capabilities in large-scale corporate projects.
• Embed Copilot into multidisciplinary workflows to maximize efficiency.
• Leverage AI tools to enhance project management, infrastructure, and software procurement.
• Deploy AI-based strategies to refine planning, estimation, and time management.
• Identify practical AI applications in industry-specific contexts like oil and gas.

Course Format

• Interactive lectures and discussions.
• Practical exercises and case studies.
• Live laboratory demonstrations of AI tools and Copilot workflows.

Course Customization Options

• To arrange a customized training session for this course, please get in touch with us.

Cursor is a sophisticated AI-powered development environment that empowers engineers to extend, fine-tune, and customize its coding intelligence to meet specialized use cases and enterprise workflows.

This instructor-led live training (available online or onsite) is designed for advanced developers and AI engineers who aim to craft tailored prompt systems, refine model behaviour, and construct custom extensions for internal development automation.

Upon completion of this training, participants will be able to:

• Design and test sophisticated prompt templates to ensure precise AI behaviour.
• Connect Cursor to internal APIs and knowledge bases to enable context-aware code generation.
• Develop fine-tuned or domain-adapted AI models tailored for specific 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 optimization labs.
• Practical projects integrating Cursor with real-world enterprise systems.

Customization Options

• This course can be tailored to align with specific internal architectures, AI frameworks, or security compliance requirements.

This instructor-led, live training in India (online or onsite) is designed for advanced-level participants who wish to customize GitHub Copilot for team projects, utilize 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:

• Customize 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.
• Optimize team collaboration using AI-powered tools.
• Manage and troubleshoot Copilot settings and permissions effectively.

This instructor-led, live training session India (offered online or onsite) is designed for developers looking to utilize GitHub Copilot Agent Mode for autonomous feature development, automated testing, and managing larger coding assignments.

By the conclusion 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 frameworks.

GitHub Copilot acts as an AI-powered coding assistant designed to automate development tasks, including critical DevOps operations such as creating YAML configurations, GitHub Actions, and deployment scripts.

This instructor-led, live training (available online or onsite) is tailored for beginner to intermediate-level professionals who aim to utilize GitHub Copilot to streamline DevOps tasks, enhance automation, and boost overall productivity.

By the conclusion of this training, participants will be equipped to:

• Utilize GitHub Copilot to assist with shell scripting, configuration, and CI/CD pipelines.
• Harness AI code completion features within YAML files and GitHub Actions.
• Accelerate testing, deployment, and automation workflows.
• Apply Copilot responsibly by understanding AI limitations and adhering to best practices.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and hands-on practice.
• Practical implementation within a live-lab environment.

Customization Options

• For tailored training requirements for this course, please reach out to us to arrange a session.

This instructor-led, live training (online or onsite) is aimed at intermediate-level software developers who wish to boost productivity and code quality using AI-assisted coding with Cursor.

By the end of this training, participants will be able to:

• Set up and configure Cursor for AI-assisted software development.
• Connect Cursor with Git repositories and integrate it into development workflows.
• Utilise natural language inputs to generate, debug, and optimise code.
• Harness AI capabilities for refactoring, documentation, and testing tasks.

Cursor is an AI-driven development environment designed to boost productivity and reliability within data and machine learning workflows. It achieves this through intelligent code generation, context-aware suggestions, and streamlined documentation processes.

This instructor-led training, available both online and onsite, is targeted at intermediate-level data and ML professionals who aim to incorporate Cursor into their daily routines. The goal is to facilitate faster prototyping, scalable pipeline development, and enhanced model operations.

Upon completion of this training, participants will be equipped to:

• Utilize Cursor to speed up notebook development and code exploration.
• Generate, refactor, and document ETL and feature engineering pipelines.
• Employ AI-assisted coding for model training, tuning, and evaluation.
• Improve reproducibility, collaboration, and operational consistency across ML workflows.

Course Format

• Interactive lectures and live demonstrations.
• Practical, hands-on exercises conducted in live coding environments.
• Case studies demonstrating the integration of Cursor with ML pipelines and model ops tools.

Course Customization Options

• This training can be customized to align with specific frameworks such as TensorFlow, PyTorch, or scikit-learn, or to suit your organization's MLOps platforms.

Cursor is an AI-driven code editor built to improve developer productivity through smart code completions, context-aware edits, and adaptive support.

This instructor-led training, available online or onsite, targets beginner-level developers and engineering teams looking to streamline their coding workflows and safely harness AI suggestions for better efficiency.

After completing this training, participants will be able to:

• Install and set up 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 lectures and discussions.
• Hands-on demonstrations and guided exercises.
• Real-world coding challenges and lab practice using Cursor.

Customization Options

• This course can be tailored to specific programming languages or frameworks used by your team.

Cursor is an 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 online or onsite) is tailored for intermediate-level technical professionals aiming to embed Cursor into their team environments to improve collaboration, streamline review processes, and uphold 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.

Format of the Course

• 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 Customization Options

• The course can be adapted to specific CI/CD platforms, repository tools, or enterprise security requirements.

This instructor-led, live training in India (online or onsite) is designed for beginner to intermediate-level developers who wish to learn how to utilize the capabilities of GitHub Copilot effectively within modern development workflows.

This instructor-led, live training in India (online or onsite) is designed for intermediate to advanced participants who aim to optimize team workflows, improve collaborative coding practices, and effectively manage Copilot usage in multi-developer settings.

Upon completing this training, participants will be capable of:

• Configuring GitHub Copilot for team environments.
• Using Copilot to strengthen collaborative coding practices.
• Optimizing team workflows through Copilot’s capabilities.
• Managing Copilot’s integration within multi-developer projects.
• Ensuring consistent code quality and standards across teams.
• Leveraging advanced Copilot features tailored to team-specific requirements.
• Integrating Copilot with other collaborative tools for enhanced efficiency.

This instructor-led live training in India (online or onsite) is tailored for beginner-level developers aiming to boost their coding efficiency with Tabnine.

By the end of this training, participants will be able to:

• Install and set up Tabnine in their preferred IDE.
• Leverage Tabnine's autocomplete features to accelerate coding.
• Customize Tabnine's settings for optimal assistance.
• Understand how Tabnine's AI learns from their code to offer better suggestions.

This instructor-led, live training in India (online or at your premises) targets advanced developers and team leads keen on mastering the advanced features of Tabnine.

By the conclusion 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.

This instructor-led, live training in India (online or onsite) is aimed at developers ranging from novices to experts who wish to leverage 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.

This instructor-led, live training in India (online or onsite) is designed for intermediate-level Python developers and data scientists who wish to boost their productivity with the help of Tabnine.

Upon completing this training, participants will be able to:

• Install and configure Tabnine in their Python development environment.
• Use Tabnine's autocomplete features to write Python code more efficiently.
• Customize Tabnine's behavior to fit their coding style and project needs.
• Understand how Tabnine's AI model works specifically with Python code.