AI-Augmented Test Generation and Quality Engineering Training Course

This advanced program on Thailand delves into GitHub Copilot and AI applications for corporate infrastructure. It empowers managers to optimize project oversight, streamline operational workflows, and strengthen decision-making through AI tools, with a particular emphasis on managing large-scale projects.

This instructor-led training in Thailand equips advanced developers to master prompt engineering, fine-tuning, and custom tooling within Cursor. Participants will design precise AI behaviors, integrate internal knowledge bases, and build secure, domain-adapted extensions for enterprise workflows.

This live, instructor-led training in Thailand (available online or on-site) is designed for advanced-level participants looking to customize GitHub Copilot for team initiatives, exploit its advanced features, and integrate it fluidly into CI/CD pipelines to amplify collaboration and productivity.

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

• Adapt GitHub Copilot to fit specific project needs and team workflows.
• Deploy Copilot’s advanced features for handling complex coding tasks.
• Integrate GitHub Copilot into CI/CD pipelines and collaborative settings.
• Enhance team synergy using AI-driven tools.
• Administer and resolve issues related to Copilot settings and permissions.

This instructor-led, live training in Thailand (available online or onsite) is tailored for developers looking to utilize GitHub Copilot Agent Mode to autonomously build features, run tests, and manage larger coding tasks.

By the end of this training, participants will be equipped to activate Agent Mode, plan and iterate within the agent loop, execute terminal commands, and implement enterprise governance strategies.

This live, instructor-led training (online or onsite) targets intermediate software developers aiming to enhance productivity and code quality by employing AI-assisted coding techniques with Cursor.

By the end of the session, learners will be capable of:

• Installing and configuring Cursor for AI-driven software development.
• Integrating Cursor with Git repositories and existing development workflows.
• Generating, debugging, and optimizing code using natural language.
• Harnessing AI capabilities for refactoring, documentation, and testing.

This instructor-led course at Thailand presents Cursor as an AI-enabled environment for accelerating data and ML operations. Learners will discover how to optimize notebook development, ETL pipelines, and model management through hands-on exercises that boost productivity and ensure operational uniformity.

This instructor-led training in Thailand assists developers in adopting Cursor, an AI-powered editor that elevates productivity through smart completions and context-aware edits. Participants acquire practical skills in refactoring, secure review of AI suggestions, and team collaboration to streamline workflows.

This live, instructor-led training in Thailand enables teams to integrate Cursor for streamlined collaboration and code reviews. Participants 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 live, instructor-led training held in Thailand (either online or on-site) is tailored for beginner to intermediate developers looking to master the effective use of GitHub Copilot within modern development practices.

This live, instructor-led training in Thailand (available online or onsite) targets intermediate to advanced participants aiming to optimize team workflows, refine collaborative coding practices, and manage Copilot usage effectively in multi-developer settings.

By the end of this session, participants will be prepared to:

• Set up GitHub Copilot for team environments.
• Use Copilot to enhance collaborative coding practices.
• Improve team workflows by utilizing Copilot’s features.
• Manage Copilot’s integration in multi-developer projects.
• Ensure consistent code quality and standards across teams.
• Utilize advanced Copilot features for specific team needs.
• Integrate Copilot with other collaborative tools for greater efficiency.

This live, instructor-led training in Thailand (online or on-site) is designed for novice developers aiming to enhance their coding efficiency through the use of Tabnine.

By the conclusion of this session, participants will be capable of:

• Installing and setting up Tabnine in their preferred IDE.
• Utilizing Tabnine's autocomplete features to expedite coding.
• Adjusting Tabnine's configuration for optimal support.
• Understanding how Tabnine's AI learns from user code to offer superior suggestions.

This instructor-led, live training in Thailand (delivered online or onsite) is designed for advanced developers and team leads seeking to harness the full potential of Tabnine's advanced features.

By the conclusion of this program, participants will be capable of:

• Implementing Tabnine in intricate software projects.
• Customizing and training Tabnine's AI models for specialized applications.
• Integrating Tabnine into collaborative team workflows and development pipelines.
• Improving code integrity and accelerating development velocity through Tabnine's insights.

This live, instructor-led training held in Thailand (whether online or on-site) targets developers of all levels, from newcomers to experts, who aim to utilize AI for code generation via Tabnine.

By the end of this program, attendees will be capable of:

• Understanding the core principles of AI-powered code generation.
• Installing and configuring Tabnine in their development setup.
• Using Tabnine for effective code completion and error fixing.
• Developing and training custom AI models with Tabnine for niche applications.

This instructor-led live training, available Thailand (online or onsite), is tailored for intermediate-level Python developers and data scientists aiming to enhance productivity through Tabnine.

By the end of the session, 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.
• Adjust Tabnine's behavior to suit their coding style and project needs.
• Comprehend the operation of Tabnine's AI model in relation to Python code.