From Idea to Production with Claude Code Training Course

GitHub Copilot is an AI-driven code completion tool designed to boost development speed while enhancing quality and productivity. When combined with Artificial Intelligence applications in projects, infrastructure, and software management, managers can utilize AI to optimize resource allocation, streamline workflows, and improve decision-making processes.

This instructor-led live training (available online or onsite) is tailored for advanced-level managers who wish to deepen their understanding of GitHub Copilot and explore practical AI applications within corporate environments. The course includes 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.

Format of the Course

• Interactive lecture and discussion.
• 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.

Cursor is a sophisticated AI-driven development environment that empowers engineers to extend, fine-tune, and customize its coding intelligence to suit specialized scenarios and enterprise workflows.

This instructor-led live training, available online or onsite, is designed for advanced developers and AI engineers aiming to craft tailored prompt systems, fine-tune model behaviours, and develop custom extensions for internal development automation.

Upon completing this training, participants will be able to:

• Design and test advanced prompt templates to achieve precise AI behaviour.
• Integrate Cursor with internal APIs and knowledge bases to enable context-aware code generation.
• Develop fine-tuned or domain-adapted AI models tailored to specific tasks.
• Construct and deploy custom tools or adapters that securely enhance Cursor’s functionality.

Course Format

• Technical presentations and guided demonstrations.
• Hands-on development sessions 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 standards.

This instructor-led, live training in Malaysia (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 Malaysia (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.

GitHub Copilot serves as an AI-driven coding assistant designed to streamline development activities, particularly DevOps operations like crafting YAML configurations, GitHub Actions, and deployment scripts.

This instructor-led live training, available both online and onsite, is tailored for beginners to intermediate professionals aiming to utilise GitHub Copilot to optimise DevOps tasks, enhance automation, and increase overall productivity.

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

• Leveraging GitHub Copilot to support shell scripting, configuration management, and CI/CD pipelines.
• Harnessing AI code completion features within YAML files and GitHub Actions.
• Speeding up testing, deployment, and automation processes.
• Applying Copilot responsibly, with a clear grasp of AI limitations and best practices.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical practice.
• Hands-on implementation in a live laboratory environment.

Course Customisation Options

• For bespoke training arrangements, please get in touch with us.

This guided live training session, available either online or at your location, is designed for software developers with intermediate experience who aim to enhance their coding productivity and quality through AI-assisted development using Cursor.

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

• Set up and configure Cursor to support AI-assisted software development.
• Connect Cursor with Git repositories and streamline development workflows.
• Utilise natural language commands to create, debug, and optimise code.
• Apply AI features for code refactoring, generating documentation, and conducting testing.

Cursor is an intelligent, AI-driven development environment designed to boost productivity and reliability in data and machine learning workflows. It offers capabilities such as intelligent code generation, context-aware suggestions, and streamlined documentation processes.

This live training session, led by an instructor and available online or onsite, targets intermediate-level data and ML professionals looking to integrate Cursor into their daily routines. The course focuses on accelerating prototyping, enabling scalable pipeline development, and improving model operations.

Upon completing this training, participants will be equipped to:

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

Course Format

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

Customization Options

• The training can be customized to align with specific frameworks such as TensorFlow, PyTorch, or scikit-learn, or tailored to your organization’s existing MLOps platforms.

Cursor 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 Customization Options

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

Cursor 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 onsite) 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.

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 Malaysia (online or onsite) is designed for beginner to intermediate developers who want to learn how to effectively use GitHub Copilot’s capabilities within modern development workflows.

This instructor-led, live training in Malaysia (online or onsite) is aimed at intermediate-level to advanced-level 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.

This instructor-led, live training in Malaysia (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.
• Utilize 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 Malaysia (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.

This instructor-led, live training in Malaysia (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.
• Utilise Tabnine for efficient code completion and error correction.
• Create and train custom AI models with Tabnine for specialised tasks.

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

By the end of 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.