LLMs for Code Understanding, Refactoring, and Documentation Training Course

This advanced module on France delves into GitHub Copilot and AI applications tailored for corporate infrastructure. It empowers managers with the skills necessary to refine project management, optimize workflows, and improve decision-making through AI tools, with a particular emphasis on managing large-scale enterprise projects.

This instructor-led course on France enables advanced developers to master prompt engineering, fine-tuning, and custom tooling within Cursor. Learners will refine precise AI behaviors, incorporate internal knowledge bases, and construct secure, domain-adapted extensions suited for enterprise workflows.

This instructor-led, live training in France (online or onsite) is aimed at 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 in France (online or onsite) is designed for 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.

This instructor-led, live training, available online or onsite, targets intermediate-level software developers aiming to increase productivity and code quality through AI-assisted coding with Cursor.

Upon completing this training, participants will be able to:

• Install and configure Cursor for AI-assisted software development.
• Connect Cursor with Git repositories and development workflows.
• Utilize natural language to generate, debug, and optimize code.
• Apply AI capabilities for refactoring, documentation, and testing.

This live, instructor-led training in France presents Cursor as an AI-enhanced environment for accelerating data and ML operations. Through practical exercises focused on improving productivity and operational consistency, participants will learn to streamline notebook development, ETL pipelines, and model management.

This live, instructor-led course in France assists developers in adopting Cursor, an AI-driven editor that enhances productivity through intelligent completions and context-aware edits. Learners acquire practical skills in refactoring, secure evaluation of AI suggestions, and team collaboration to optimize their workflows.

This live, instructor-led training on France empowers teams to adopt Cursor for streamlined collaboration and efficient code reviews. Discover how to manage workspaces, automate AI-assisted pull requests, apply governance frameworks, and link Cursor to CI/CD pipelines for sustained quality assurance.

This instructor-led, live training in France (online or onsite) is aimed at beginner-level 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 session in France (online or onsite) targets intermediate to advanced professionals aiming to refine team workflows, strengthen collaborative coding habits, and effectively oversee Copilot usage within multi-developer settings.

Upon completion of this training, participants will be capable of:

• Configuring GitHub Copilot for team-based environments.
• Applying Copilot to improve collaborative coding techniques.
• Refining team workflows through Copilot’s capabilities.
• Administering Copilot’s integration across multi-developer initiatives.
• Ensuring uniform code quality and standards among team members.
• Harnessing advanced Copilot features tailored to specific team requirements.
• Integrating Copilot with other collaborative tools to maximize efficiency.

This instructor-led live training in France (online or onsite) is targeted at beginner-level developers looking to enhance their coding efficiency with Tabnine.

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

• Install and configure Tabnine in their preferred IDE.
• Use Tabnine's autocomplete features to speed up coding.
• Customize Tabnine's settings for optimal assistance.
• Understand how Tabnine's AI learns from their code to provide better suggestions.

This instructor-led live training in France (online or onsite) is designed for advanced developers and team leads who wish to master the 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.

This instructor-led, live training in France (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 France (online or onsite) is designed for intermediate-level Python developers and data scientists aiming to enhance their productivity with Tabnine.

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

• Install and configure Tabnine within their Python development environment.
• Utilize Tabnine's autocomplete capabilities to write Python code more efficiently.
• Customize Tabnine's behavior to align with their coding style and project requirements.
• Gain insight into how Tabnine's AI model operates specifically with Python code.