AI-Driven Software Development Lifecycle (SDLC) Training Course

This advanced training on India focuses on GitHub Copilot and AI applications within corporate infrastructure. It empowers managers with the skills to optimize project management, streamline workflows, and enhance decision-making through AI tools, with a particular emphasis on large-scale projects.

This instructor-led training in India enables advanced developers to gain mastery over prompt engineering, fine-tuning, and custom tooling within Cursor. Participants will learn to define precise AI behaviors, integrate internal knowledge bases, and construct secure, domain-adapted extensions for enterprise workflows.

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 in India (online or onsite) is aimed at developers who wish to use GitHub Copilot Agent Mode to build features autonomously, 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 live, instructor-led training, accessible online or onsite, targets intermediate software developers aiming to improve productivity and code quality via AI-assisted coding with Cursor.

By the end of the program, participants will be capable of:

• Installing and configuring Cursor for AI-driven software development.
• Linking Cursor to Git repositories and development processes.
• Using natural language to generate, debug, and optimize code.
• Utilizing AI for refactoring, documentation creation, and testing.

This instructor-led training in India introduces Cursor as an AI-powered environment designed to accelerate data and ML workflows. Through practical exercises, participants will learn to streamline notebook development, ETL pipelines, and model operations, thereby enhancing overall productivity and operational consistency.

This instructor-led session in India guides developers in mastering Cursor, an AI-powered editor that drives productivity through smart completions and contextual editing. Participants develop hands-on proficiency in refactoring, safe AI suggestion validation, and team collaboration to refine their workflows.

This live, instructor-led training in India empowers teams to integrate Cursor, thereby streamlining collaboration and code review processes. You will learn to manage workspaces, automate AI-assisted pull requests, enforce governance policies, and link Cursor to CI/CD pipelines to maintain consistent quality.

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.