GitHub Copilot for DevOps Automation and Productivity Training Course

GitHub Copilot is an AI-driven code completion assistant designed to accelerate development while enhancing quality and productivity. When integrated with AI applications across projects, infrastructure, and software, managers can harness artificial intelligence to optimize resource distribution, streamline operational workflows, and improve decision-making processes.

This instructor-led training, available online or onsite, targets advanced-level managers seeking to deepen their expertise in GitHub Copilot while exploring practical AI applications within corporate settings. The course features examples pertinent to large-scale projects and industries such as oil and gas.

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

• Applying advanced Copilot capabilities in large-scale corporate projects.
• Integrating Copilot into multidisciplinary workflows to maximize efficiency.
• Utilizing AI tools to optimize project management, infrastructure, and software procurement.
• Implementing AI-driven strategies to enhance planning, estimation, and time management.
• Identifying practical AI applications in industry-specific contexts, such as oil and gas.

Course Format

• Interactive lectures and discussions.
• Hands-on exercises and case studies.
• Live-lab demonstrations of AI tools and Copilot workflows.

Course Customization Options

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

This instructor-led, live training in Italy (online or onsite) is designed for advanced participants who want to customize GitHub Copilot for team initiatives, exploit its advanced functionalities, and seamlessly integrate it into CI/CD pipelines to boost collaboration and productivity.

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

• Customize GitHub Copilot to align with specific project requirements and team workflows.
• Utilize Copilot’s advanced features for tackling complex coding challenges.
• Integrate GitHub Copilot into CI/CD pipelines and collaborative environments.
• Enhance team collaboration through AI-powered tools.
• Effectively manage and troubleshoot Copilot settings and permissions.

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) represents a methodology that leverages machine learning and advanced analytics to automate and enhance IT operations, with a specific focus on monitoring, incident detection, and response processes.

This instructor-led live training, available both online and onsite, is designed for IT operations professionals at an intermediate level who aim to implement AIOps techniques. The goal is to correlate metrics and logs, minimize alert noise, and boost observability through intelligent automation.

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

• Grasping the core principles and architectural frameworks of AIOps platforms.
• Correlating data from logs, metrics, and traces to pinpoint root causes.
• Mitigating alert fatigue via intelligent filtering and noise suppression.
• Utilizing open-source or commercial tools to automate the monitoring and response to incidents.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practical applications.
• Hands-on implementation within a live laboratory environment.

Customization Options

• For a tailored training experience for this course, please contact us to make arrangements.

Developing an AIOps pipeline exclusively with open-source tools empowers teams to create affordable 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 who want to build and deploy a comprehensive AIOps pipeline using tools such as Prometheus, ELK, Grafana, and custom machine learning models.

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

• Architecting an AIOps solution using solely open-source components.
• Gathering and standardizing data from logs, metrics, and traces.
• Implementing machine learning models to identify anomalies and predict incidents.
• Automating alerts and remediation processes using open tooling.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical activities.
• Hands-on implementation within a live-lab environment.

Customization Options

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

This instructor-led, live training in Italy (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.

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 Italy (online or onsite) targets beginner to intermediate developers who wish to learn how to effectively utilize GitHub Copilot's capabilities within modern development workflows.

This instructor-led, live training in Italy (available online or onsite) targets intermediate to advanced participants who want to optimize team workflows, enhance collaborative coding practices, and manage Copilot usage effectively in multi-developer environments.

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

• Configure GitHub Copilot for team environments.
• Use 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 Italy (online or onsite) is designed for intermediate QA engineers, developers, and team leads who aim to utilize GitHub Copilot for more efficient debugging, enhanced code quality, and streamlined code reviews.

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

• Configure GitHub Copilot specifically for debugging and code review tasks.
• Utilize Copilot to swiftly detect and fix bugs.
• Improve code quality through AI-guided recommendations.
• Optimize code review workflows using Copilot’s features.
• Foster effective teamwork by integrating Copilot into collaborative settings.

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

Upon completing this training, participants will be capable of:

• Installing and configuring GitHub Copilot for Python development.
• Utilizing Copilot to write efficient Python code.
• Debugging Python applications using AI-generated insights.
• Automating repetitive coding tasks to enhance workflow efficiency.
• Leveraging 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.

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

• Configure Prometheus and Grafana for observability across 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.

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 Italy (online or onsite) targets intermediate-level professionals looking to master GitHub Copilot for complex coding scenarios, boost their productivity, and seamlessly incorporate Copilot into their daily development processes.

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

• Maximize the effectiveness of GitHub Copilot for advanced programming tasks.
• Produce code that is more efficient, reliable, and easier to maintain using Copilot's suggestions.
• Integrate GitHub Copilot into their preferred Integrated Development Environments (IDEs) and workflows.
• Apply Copilot for debugging and code refactoring activities.
• Grasp the limitations and ethical implications of utilizing AI-assisted coding tools.

This live, instructor-led training in Italy (online or on-site) is designed for beginner-level developers who want 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.