CI/CD for AI: Automating Docker-Based Model Builds and Deployments Training Course

AI-driven deployment orchestration is a method that leverages machine learning and automation to guide deployment strategies, detect anomalies, and initiate automatic rollbacks when necessary. This instructor-led, live training (available online or onsite) is designed for intermediate-level professionals who aim to enhance their deployment pipelines with AI-powered decision-making and resilience capabilities for government operations. Upon completing this training, participants will be able to: - Implement AI-assisted rollout strategies for safer deployments. - Predict deployment risks using machine learning-driven insights. - Integrate automated rollback workflows based on anomaly detection. - Enhance observability to support intelligent orchestration. **Format of the Course** - Instructor-led demonstrations with technical deep dives. - Hands-on scenarios focused on deployment experimentation. - Practical labs simulating real-world orchestration challenges. **Course Customization Options** - Customized integrations, toolchain support, or workflow alignment for government can be arranged upon request.

AI for DevOps is the application of artificial intelligence to enhance continuous integration, testing, deployment, and delivery processes with intelligent automation and optimization techniques.

This instructor-led, live training (online or onsite) is designed for intermediate-level DevOps professionals who wish to integrate AI and machine learning into their CI/CD pipelines to improve speed, accuracy, and quality.

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

• Integrate AI tools into CI/CD workflows for intelligent automation.
• Apply AI-based testing, code analysis, and change impact detection.
• Optimize build and deployment strategies using predictive insights.
• Implement traceability and continuous improvement using AI-enhanced feedback loops.

Format of the Course for Government

• Interactive lecture and discussion.
• Numerous exercises and practice sessions.
• 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 is a rapidly advancing field that addresses the complexities of modern IT environments, particularly those utilizing cloud architectures. The AIOps Foundation course provides a thorough introduction to the concepts, technologies, and practices associated with integrating artificial intelligence into IT operations.

This program delves into the background of AIOps, its fundamental principles, essential tools, and the organizational challenges that IT teams face when adopting these innovative approaches.

The training culminates in an exam. Successfully passing this exam awards participants the globally recognized AIOps Foundation certification, which remains valid for three years.

Who is it for?

This course is tailored for professionals and managers involved in:

IT operations

DevOps and Site Reliability Engineering (SRE)

Cloud architecture

Data analysis and data science

Software development

IT security

Product and project management

This comprehensive training is designed to enhance the capabilities of individuals working in these areas, providing them with the knowledge and skills necessary to effectively leverage AIOps technologies for government and other critical sectors.

Artificial Intelligence for IT Operations (AIOps) is increasingly utilized to predict incidents before they occur and automate root cause analysis (RCA) to minimize downtime and accelerate resolution. This instructor-led, live training (available online or onsite) is designed for advanced-level IT professionals who wish to implement predictive analytics, automate remediation processes, and design intelligent RCA workflows using AIOps tools and machine learning models for government. By the end of this training, participants will be able to: - Build and train machine learning 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. - Extensive exercises and practice sessions. - Hands-on implementation in a live-lab environment. **Course Customization Options** - To request a customized training for this course, please contact us to arrange.

The AI Ops Advanced course builds upon foundational AIOps principles to offer practical, hands-on experience with real-world tools, advanced machine learning techniques, automation workflows, and operational design patterns. It equips participants to construct, configure, fine-tune, and extend AIOps pipelines and integrations.

This instructor-led, live training (available online or on-site) is designed for intermediate to advanced IT professionals who aim to develop robust AIOps ecosystems, conduct advanced analytics, and automate operational workflows using real-world tools. The course aligns with the needs of participants in various sectors, including those for government.

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

• Correlate and normalize diverse operational data sources.
• Design and refine anomaly detection and root cause analysis models.
• Integrate AIOps with IT Service Management (ITSM) and DevOps pipelines.
• Develop closed-loop automation and predictive incident workflows.

Format of the Course

• Advanced lectures and architecture discussions.
• Hands-on labs with industry-standard tools and platforms.
• Case studies and optimization exercises.

Artificial Intelligence for IT Operations (AIOps) is the utilization of machine learning, analytics, and automation to streamline and enhance IT operations. It assists organizations in automating incident detection, correlating events, and improving operational decision-making.

This instructor-led, live training (conducted online or on-site) is designed for government IT professionals at the beginner level who wish to understand the fundamentals of applying AI and big data in IT operations to improve observability, metrics, and incident handling.

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

• Describe the evolution and importance of AIOps for government.
• Explain core technologies such as big data and machine learning within AIOps contexts.
• Identify key operational metrics and use cases for AIOps in public sector environments.
• Understand the organizational impact, implementation strategies, and challenges of deploying AIOps solutions.

Format of the Course

• Interactive lecture and discussion.
• Case study review and scenario-based discussions relevant to government operations.
• Hands-on exercises with AIOps concepts and tools tailored for government IT professionals.

AIOps (Artificial Intelligence for IT Operations) is a practice that leverages machine learning and analytics to automate and enhance IT operations, particularly in monitoring, incident detection, and response.

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

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.
• Extensive exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

An AIOps pipeline constructed entirely with open-source tools enables teams to develop cost-effective and flexible solutions for observability, anomaly detection, and intelligent alerting in production environments. This instructor-led, live training (conducted online or on-site) is designed for advanced-level engineers who aim to build and deploy an end-to-end AIOps pipeline using tools such as Prometheus, ELK, Grafana, and custom machine learning models. By the end of this training, participants will be able to: - Design an AIOps architecture utilizing only open-source components. - Collect and normalize data from logs, metrics, and traces. - Apply machine learning models to detect anomalies and predict incidents. - Automate alerting and remediation processes using open tooling. **Format of the Course** - Interactive lecture and discussion. - Extensive exercises and practice sessions. - Hands-on implementation in a live-lab environment. **Course Customization Options for Government** - To request a customized training for government, please contact us to arrange.

AI-powered QA automation enhances traditional testing methods by generating intelligent test cases, optimizing regression coverage, and integrating quality gates into CI/CD pipelines to ensure scalable and reliable software delivery for government. This instructor-led, live training (online or onsite) is designed for intermediate-level QA and DevOps professionals who aim to leverage AI tools to automate and scale quality assurance in continuous integration and deployment workflows for government. By the end of this training, participants will be able to: - Generate, prioritize, and maintain tests using AI-driven automation platforms. - Integrate intelligent QA gates into CI/CD pipelines to prevent regressions. - Use AI for exploratory testing, defect prediction, and test flakiness analysis. - Optimize testing time and coverage across fast-moving agile projects. **Format of the Course** - Interactive lecture and discussion. - Extensive exercises and practice sessions. - Hands-on implementation in a live-lab environment. **Course Customization Options** - To request a customized training for this course, please contact us to arrange.

GitHub Copilot is an AI-powered coding assistant designed to help automate various development tasks, including DevOps operations such as writing YAML configurations, GitHub Actions, and deployment scripts.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level professionals who wish to utilize GitHub Copilot to streamline DevOps tasks, enhance automation, and increase productivity for government and other public sector workflows.

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

• Use GitHub Copilot to assist with shell scripting, configuration, and CI/CD pipelines.
• Leverage AI code completion in YAML files and GitHub Actions.
• Accelerate testing, deployment, and automation workflows.
• Apply Copilot responsibly with an understanding of AI limitations and best practices for government use.

Format of the Course

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

Course Customization Options

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

DevSecOps with AI is the practice of integrating artificial intelligence into DevOps pipelines to proactively identify vulnerabilities, enforce security policies, and automate response actions throughout the software delivery lifecycle.

This instructor-led, live training (online or onsite) is designed for intermediate-level DevOps and security professionals who seek to apply AI-based tools and practices to enhance security automation across development and deployment pipelines.

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

• Integrate AI-driven security tools into CI/CD pipelines.
• Utilize static and dynamic analysis powered by AI to detect issues at earlier stages.
• Automate the detection of secrets, code vulnerability scanning, and dependency risk analysis.
• Implement proactive threat modeling and policy enforcement using intelligent techniques.

Format of the Course

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

Course Customization Options for Government

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

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 (online or onsite) is designed for intermediate-level enterprise IT teams who wish to integrate AIOps tools into their existing observability stack and operational workflows for government. 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 Mean Time to Resolution (MTTR), and improve operational efficiency at enterprise scale. **Format of the Course** - Interactive lecture and discussion. - Extensive exercises and practice sessions. - Hands-on implementation in a live-lab environment. **Course Customization Options** - To request a customized training for this course, please contact us to arrange.

Prometheus and Grafana are widely utilized tools for observability in modern infrastructure. When augmented with machine learning, these tools provide predictive and intelligent insights that enhance the automation of operations decisions. This instructor-led, live training (available online or on-site) is designed for intermediate-level observability professionals who aim to modernize their monitoring systems by integrating AIOps practices using Prometheus, Grafana, and machine learning techniques. By the end of this training, participants will be able to: - Configure Prometheus and Grafana for comprehensive observability across systems and services. - Collect, store, and visualize high-quality time series data. - Apply machine learning models for anomaly detection and forecasting. - Develop intelligent alerting rules based on predictive insights. **Format of the Course:** - Interactive lecture and discussion. - Extensive exercises and practice sessions. - Hands-on implementation in a live-lab environment. **Course Customization Options:** - To request a customized training program for government, please contact us to arrange.

Large Language Models (LLMs) and autonomous agent frameworks such as AutoGen and CrewAI are transforming how DevOps teams automate tasks like change tracking, test generation, and alert triage by simulating human-like collaboration and decision-making processes.

This instructor-led, live training (available online or onsite) is designed for advanced-level engineers who aim to design and implement DevOps automation workflows powered by LLMs and multi-agent systems for government applications.

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

• Integrate LLM-based agents into CI/CD workflows to enhance smart automation capabilities.
• Automate test generation, commit analysis, and change summaries using these advanced agents.
• Coordinate multiple agents for effective alert triaging, response generation, and DevOps recommendations.
• Build secure and maintainable agent-powered workflows utilizing open-source frameworks.

Format of the Course

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

Course Customization Options

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

Upon completion of this course, participants will be able to: - Gain a comprehensive understanding of the architecture and functionality of modern Large Language Models (LLMs). - Create structured and robust technical prompts for styling, testing, refactoring, and automated quality assurance. - Develop AI-aware wrappers and microservices that integrate seamlessly within enterprise development ecosystems for government. - Implement comprehensive Retrieval-Augmented Generation (RAG) pipelines for organizational knowledge retrieval. - Manage the security, privacy, and audit aspects of AI-driven code and data interactions.