GitHub Copilot for DevOps Automation and Productivity Training Course

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

This instructor-led, live training (available online or onsite) targets advanced-level managers who wish to deepen their understanding of GitHub Copilot while exploring practical AI applications in corporate environments, with 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.

This instructor-led, live training in Taiwan (available online or onsite) is targeted at advanced-level participants who aim to customize GitHub Copilot for team projects, leverage its advanced features, and seamlessly integrate it into CI/CD pipelines to enhance 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.

AIOps (Artificial Intelligence for IT Operations) is increasingly being used to predict incidents before they occur and automate root cause analysis (RCA) to minimize downtime and accelerate resolution.

This instructor-led, live training (online or onsite) is aimed at advanced-level IT professionals who wish to implement predictive analytics, automate remediation, and design intelligent RCA workflows using AIOps tools and machine learning models.

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

• Build and train ML models to detect patterns leading to system failures.
• Automate RCA workflows based on multi-source log and metric correlation.
• Integrate alerting and remediation processes into existing platforms.
• Deploy and scale intelligent AIOps pipelines in production environments.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

AIOps (Artificial Intelligence for IT Operations) is a practice that applies machine learning and analytics to automate and improve IT operations, particularly in the areas of monitoring, incident detection, and response.

This instructor-led, live training (online or onsite) is aimed at intermediate-level IT operations professionals who wish to implement AIOps techniques to correlate metrics and logs, reduce alert noise, and improve observability through intelligent automation.

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

• Understand the principles and architecture of AIOps platforms.
• Correlate data across logs, metrics, and traces to identify root causes.
• Reduce alert fatigue through intelligent filtering and noise suppression.
• Use open-source or commercial tools to monitor and respond to incidents automatically.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

By leveraging exclusively open-source tools, teams can engineer cost-efficient and adaptable solutions for observability, anomaly detection, and intelligent alerting within production environments.

This instructor-led live training (available online or onsite) targets advanced engineers aiming to design and deploy a comprehensive AIOps pipeline utilizing tools such as Prometheus, ELK, Grafana, and custom machine learning models.

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

• Architect an AIOps system composed entirely of open-source components.
  
• Gather and standardize data derived from logs, metrics, and traces.
  
• Implement machine learning models to identify anomalies and forecast incidents.
  
• Streamline alerting and remediation processes using open-source tooling.
  

Course Format

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

Customization Options

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

This instructor-led live training in Taiwan (online or onsite) targets 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.

Enterprise AIOps platforms such as Splunk, Moogsoft, and Dynatrace offer robust capabilities for detecting anomalies, correlating alerts, and automating responses across large-scale IT environments.

This instructor-led, live training (available online or onsite) is designed for intermediate-level enterprise IT teams looking to integrate AIOps tools into their existing observability stacks and operational workflows.

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

• Configure and integrate Splunk, Moogsoft, and Dynatrace into a unified AIOps architecture.
• Correlate metrics, logs, and events across distributed systems using AI-driven analysis.
• Automate incident detection, prioritization, and response with built-in and custom workflows.
• Optimize performance, reduce MTTR, and improve operational efficiency at enterprise scale.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Taiwan (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 in Taiwan (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 Taiwan (online or onsite) is aimed at intermediate-level QA engineers, developers, and team leads who wish to leverage GitHub Copilot for more efficient debugging, code quality enhancement, and streamlined code review.

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

• Set up GitHub Copilot for debugging and code review purposes.
• Use Copilot to identify and resolve bugs efficiently.
• Enhance code quality with AI-assisted suggestions.
• Streamline code review processes with Copilot's capabilities.
• Collaborate effectively using Copilot in team environments.

This instructor-led, live training in Taiwan (online or onsite) targets intermediate-level front-end developers who wish to use GitHub Copilot to automate repetitive coding tasks, improve UI/UX design, and streamline front-end workflows.

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

• Set up GitHub Copilot for front-end development projects.
• Leverage Copilot to generate HTML, CSS, and JavaScript code efficiently.
• Improve UI/UX design processes using AI-generated code suggestions.
• Enhance front-end workflows with practical Copilot integration strategies.
• Troubleshoot and debug front-end code using Copilot assistance.

This instructor-led, live training in Taiwan (online or onsite) is aimed at beginner-level to intermediate-level Python developers who wish to leverage GitHub Copilot for Python-specific tasks, debugging, and implementing machine learning workflows.

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

• Set up and configure GitHub Copilot for Python development.
• Leverage Copilot to write efficient Python code.
• Debug Python applications using AI-generated suggestions.
• Automate repetitive coding tasks and improve workflow efficiency.
• Utilize Copilot for implementing machine learning projects in Python.

Prometheus and Grafana are widely adopted tools for observability in modern infrastructure, while machine learning enhances these tools with predictive and intelligent insights to automate operations decisions.

This instructor-led, live training (online or onsite) is aimed at intermediate-level observability professionals who wish to modernize their monitoring infrastructure by integrating AIOps practices using Prometheus, Grafana, and ML techniques.

Upon completing this training, participants will be able to:

• Configure Prometheus and Grafana to deliver comprehensive observability across various systems and services.
• Collect, store, and visualize high-quality time series data.
• Apply machine learning models for anomaly detection and forecasting.
• Build intelligent alerting rules based on predictive insights.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practical practice sessions.
• Hands-on implementation within a live lab environment.

Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led live training in Taiwan (online or onsite) is aimed at intermediate-level participants who wish to leverage GitHub Copilot to handle advanced coding use cases, improve productivity, and integrate Copilot into their development workflows.

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

• Optimize their use of GitHub Copilot for advanced coding tasks.
• Write more efficient, error-free, and maintainable code with Copilot suggestions.
• Integrate GitHub Copilot into their preferred IDEs and workflows.
• Utilize Copilot for debugging and code refactoring.
• Understand the limitations and ethical considerations of using AI-powered coding tools.

This instructor-led, live training in Taiwan (online or onsite) targets beginner-level developers who wish to understand GitHub Copilot's capabilities, set it up, and use it effectively to enhance their coding experience.

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

• Understand what GitHub Copilot is and how it works.
• Set up GitHub Copilot with a supported code editor.
• Use GitHub Copilot to write, refactor, and debug code faster.
• Leverage Copilot to explore coding techniques and solutions.
• Apply best practices for integrating GitHub Copilot into daily workflows.