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Advanced DevOps Certification Training Course with Gen AI in San Juan, Puerto Rico

4.4 (33100 ratings) 83895 learners [Rate this training]

Gain Advanced Hands-on DevOps and Generative AI Expertise with Instructor-Led Online Training in San Juan, Puerto Rico

  • Launch your DevOps career in San Juan, Puerto Rico, one of the fastest-growing tech roles today
  • Learn Advanced DevOps and Generative AI with expert instructors via Live Virtual Classes
  • Attend from the comfort of your home or office, flexible learning for busy professionals
  • Build job-ready skills through practical sessions and real-world DevOps tools
  • 60 Hours of interactive, instructor-led online training, career-focused and immersive
  • Join our top-rated Advanced DevOps with Gen AI training in San Juan, Puerto Rico, live, affordable, and industry-aligned

Enroll now to build hands-on DevOps and Gen AI skills with expert-led virtual classes in San Juan, Puerto Rico, and boost your career.

Advanced DevOps

Advanced DevOps Training Options in San Juan, Puerto Rico

Live-Virtual Class
  • Attend from the Comfort of Your Home: Join our instructor-led live virtual classes delivered entirely online with no travel required.
  • 60 Hours of Expert-Led Training: Gain deep knowledge through interactive sessions conducted by industry professionals on a live virtual platform.
  • Flexible Scheduling Options: Pick a schedule that suits you, either 20 sessions of 3 hours each or 15 sessions of 4 hours each.
  • Taught through real-world case studies and a capstone project, enabling hands-on implementation of CI/CD methodologies using leading DevOps tools.
  • Build Intelligent CI/CD Pipelines: Design, automate, and optimize scalable CI/CD workflows using modern DevOps tools, integrating AI to enhance monitoring, testing, and deployment efficiency.
  • Hands-On, Industry-Aligned Projects: Gain real-world experience by implementing containerized applications, automated infrastructure provisioning, GitOps deployments, and AI-enabled observability in production-like environments.
  • Lifetime Access to Learning Resources: Get unrestricted access to our Learning Management System (LMS), including class recordings, presentations, and course materials.
  • Certification on Course Completion: ā€œDevOps Engineerā€ certification granted after successful completion of course requirements and the capstone project.
  • 24x7 Lifetime Support: Access our dedicated support system anytime, even after completing the course
Date : Mar 14 May 17 (Weekend)
Time : 09:00 AM to 12:00 PM (CST)

Early Bird Price

USD 699 489
Mar 14Sat Mar 15Sun Mar 21Sat Mar 22Sun Mar 28Sat Mar 29Sun Apr 04Sat Apr 05Sun Apr 11Sat Apr 12Sun Apr 18Sat Apr 19Sun Apr 25Sat Apr 26Sun May 02Sat May 03Sun May 09Sat May 10Sun May 16Sat May 17Sun
Class Timings :
Class Date (UTC): Saturday, 14th March 2026 - Sunday, 17th May 2026
03:00 PM - 06:00 PM
(UTC)
Class Date (Local time): Saturday, 14th March 2026 - Sunday, 17th May 2026
09:00 AM - 12:00 PM (CST)
Time zone: (UTC -06:00) Central Standard Time

Advanced DevOps Certification Course Overview

The Advanced DevOps Training Program with Generative AI Certification Training in San Juan, Puerto Rico

The Advanced DevOps Training Program with Generative AI Certification Training is designed for professionals in San Juan, Puerto Rico who want to build advanced DevOps capabilities enhanced with intelligent automation. Delivered exclusively through Live Virtual Classes, this instructor-led program enables learners in San Juan, Puerto Rico to interact directly with experts, clarify concepts in real time, and apply knowledge through guided implementation sessions.

This program emphasizes extensive hands-on learning through multiple real-world projects, practical demonstrations, and industry-focused use cases. Participants in San Juan, Puerto Rico gain exposure to widely adopted DevOps technologies such as Docker, Kubernetes, Terraform, Jenkins, GitHub Actions, and Prometheus, while developing applied expertise in AI-driven DevOps automation, AIOps practices, and intelligent monitoring strategies used in enterprise environments.

The curriculum spans continuous integration and delivery pipelines, container orchestration, infrastructure provisioning, cloud-native deployment on AWS and Azure, GitOps methodologies, and Generative AI integration within DevOps processes. Learners in San Juan, Puerto Rico master essential skills required to design scalable DevOps ecosystems that combine automation, observability, and intelligent optimization.

Recognized among our popular and top-rated courses, this Live Virtual Class helps professionals in San Juan, Puerto Rico get in-demand DevOps and AI integration expertise aligned with evolving industry requirements.

Join the Live Virtual Class in San Juan, Puerto Rico today and accelerate your journey toward building AI-powered DevOps expertise with hands-on, expert-led training.

Course Outcomes

After completing this program, learners in San Juan, Puerto Rico will be able to:

  • Architect automated CI and CD workflows for modern application delivery
  • Manage containerized workloads and orchestrate clusters using Kubernetes
  • Implement infrastructure automation and configuration management practices
  • Deploy and operate applications across AWS and Azure environments
  • Apply GitOps-driven deployment strategies
  • Incorporate Generative AI and AIOps capabilities into DevOps toolchains
  • Execute enterprise-style DevOps implementations through real-world projects

What’ll You Learn

  • Advanced CI and CD implementation strategies
  • Containerization and orchestration best practices
  • Infrastructure as Code concepts using Terraform and Ansible
  • Cloud deployment models and DevOps integration
  • Monitoring, observability, and intelligent alerting systems
  • AI-enabled automation across DevOps workflows
  • Capstone execution of an end-to-end DevOps lifecycle project

Who Should Attend

  • DevOps professionals in San Juan, Puerto Rico seeking advanced automation skills
  • Cloud and infrastructure engineers
  • IT operations and system administrators
  • Developers transitioning to DevOps roles
  • Professionals preparing for industry-recognized certifications in DevOps
  • Technology professionals aiming to get in-demand cloud and AI integration skills

Why Choose Our Course

  • Delivered exclusively as Live Virtual Classes for learners in San Juan, Puerto Rico
  • One of our popular and top rated courses focused on DevOps with Generative AI
  • Strong emphasis on real-world projects and applied implementation
  • Curriculum designed to help participants master essential skills in automation and orchestration
  • Practical exposure to modern DevOps toolchains and AI-enabled monitoring
  • Structured pathway toward industry-recognized certifications and career advancement

Career & Outcomes

Organizations across finance, healthcare, retail, manufacturing, and technology sectors in San Juan, Puerto Rico and beyond are adopting DevOps and AI-driven automation practices. Completing this program prepares you for roles such as DevOps Engineer, Site Reliability Engineer, Platform Engineer, Automation Specialist, and Cloud Solutions Architect.

Professionals who combine DevOps expertise with Generative AI capabilities are increasingly valued for their ability to optimize deployment pipelines, improve system reliability, and enhance operational intelligence.

Salary Insight

DevOps professionals in San Juan, Puerto Rico with expertise in CI and CD automation, Kubernetes orchestration, cloud infrastructure, and AI-enabled monitoring are positioned for competitive compensation. As enterprises expand cloud adoption and automation strategies, demand for skilled DevOps engineers continues to grow, contributing to strong salary progression and long-term career stability.

Are there any in-person classes available in San Juan, Puerto Rico?

Currently, we do not offer in-person classes in San Juan, Puerto Rico. However, you can join our instructor-led live virtual classes from San Juan, Puerto Rico or anywhere in the world. These sessions are highly interactive and designed to closely replicate the in-person classroom experience, all from the comfort of your home or office.

The Next Steps

If you are ready to strengthen your DevOps foundation and integrate Generative AI into modern deployment environments, this Live Virtual Class in San Juan, Puerto Rico provides the structure, mentorship, and hands-on practice required to succeed. Through expert-led sessions and real-world projects, you will gain the confidence to implement scalable, intelligent DevOps solutions.

Secure your seat in the DevOps Training Program with Generative AI Certification Training in San Juan, Puerto Rico today. Act now to master essential skills, get in-demand expertise, and advance toward high-impact DevOps roles with AI-driven capabilities.

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The Advanced DevOps Certification Training with GenAI is ideal for IT enthusiasts, developers, and professionals looking to build automated, intelligent software delivery pipelines. It is best suited for:

  • Software Developers wanting to expand into DevOps
  • System Administrators transitioning to cloud and automation roles
  • IT Operations professionals seeking modern DevOps practices
  • DevOps Engineers looking to upgrade their skills with GenAI
  • Cloud Engineers wanting to integrate AI into infrastructure management
  • Freshers who want to leverage DevOps and GenAI for career growth

Whether you're starting out or advancing your career, enroll today and gain the DevOps and Generative AI expertise that sets you apart

The Advanced DevOps Certification with Generative AI training prepares you for the evolving future of software development and IT operations. It equips you with hands-on expertise in CI/CD, infrastructure as code, cloud automation, and AI-driven DevOps practices, helping you build secure, scalable, and intelligent delivery pipelines that modern organizations require.

Key reasons why this certification is valuable:

  1. Practical DevOps Experience: Work on real-world projects that simulate enterprise DevOps environments, including CI/CD pipeline creation, infrastructure automation, and production-level troubleshooting.
  2. AI-Driven Automation Skills: Learn how to integrate AI into DevOps workflows for smarter code generation, automated testing, anomaly detection, and performance monitoring.
  3. End-to-End Lifecycle Mastery: Gain exposure to the complete software delivery lifecycle using widely adopted tools such as Git, Jenkins, Docker, Kubernetes, Terraform, and Ansible.
  4. Industry-Relevant Toolset and Practices: Stay aligned with current DevOps and AI trends by learning tools and methodologies used by leading technology organizations.
  5. Career Advancement Opportunities: Strengthen your professional profile with in-demand DevOps and Generative AI skills that employers actively seek.

Whether you're starting your journey or advancing your expertise, join the program today and master future-ready DevOps skills.

Yes, the course includes extensive hands-on labs and practical exercises designed to reinforce real-world DevOps and Generative AI skills.

Learners receive detailed, step-by-step guidance through the Learning Management System to help them set up environments, configure DevOps tools, and integrate Generative AI capabilities into their workflows. The program provides access to cloud-based lab environments, allowing participants to practice with tools such as Docker, Kubernetes, Terraform, CI/CD pipelines, and AI-powered automation platforms without the need for complex local installations.

Additionally, dedicated support is available to assist learners with technical questions or challenges encountered during lab sessions, ensuring a smooth and uninterrupted learning experience.

The system requirements for this Advanced DevOps Certification Training with GenAI include:

Hardware Requirements:
  • CPU: Multi-core processor (minimum 2 cores, 4 or more recommended)
  • Memory (RAM): At least 8 GB (16 GB recommended for running Docker and Kubernetes locally)
  • Storage: Minimum 50 GB of free disk space for container images and tools
  • GPU: Not required for this course
Software Requirements:
  • Operating System: Windows 10/11, macOS, or Linux (Ubuntu 20.04+ recommended for DevOps development)
  • Programming Language: Basic proficiency in Python or Shell scripting
  • Development Tools: VS Code, Terminal/Command Line
  • Virtualization: Docker Desktop (installation guided in course)
  • Browser: Chrome or Firefox for accessing cloud consoles and GenAI tools
  • Package Management: Familiarity with pip, npm, or apt is helpful.

There are no mandatory prerequisites for taking the Advanced DevOps certification training. However, having the following knowledge will be beneficial:

  • Basic understanding of Linux/Unix commands
  • Familiarity with Git, scripting languages (Python, Bash, YAML)
  • Exposure to cloud platforms like AWS or Azure
  • Familiarity with CI/CD concepts, containers, and general IT operations will also be beneficial for deeper comprehension

No prior experience with AI tools is required; the course covers the basics of Generative AI in DevOps from the ground up.

Further, learners will be provided with self-learning refresher material on Linux, Git, and foundational DevOps concepts before beginning the live classes.

Advanced DevOps Certification Course Topics

  • Introduction to DevOps: History, Evolution & Benefits
  • DevOps Culture, Practices & Core Principles
  • DLC vs DevOps Lifecycle
  • DevOps Toolchain Overview & Tool Selection
  • Agile, Lean & DevOps Integration
  • Key Metrics: DORA Metrics, Lead Time, MTTR, Change Failure Rate
  • DevOps Transformation Roadmap
  • Introduction to AI in DevOps: Overview & Use Cases
  • Essential Linux Commands for DevOps
  • Introduction to GitHub Copilot & AI Coding Assistants
  • Setting up Copilot in VS Code & JetBrains IDEs
  • Copilot for Shell Script & Bash Generation
  • AI-Assisted Python Scripting for Automation
  • Prompt Engineering Best Practices for DevOps
  • Copilot Chat for Code Explanation & Debugging
  • AI Code Review & Suggestions
  • Copilot for Documentation Generation
  • Ethical AI Usage & Best Practices
  • Git Fundamentals: Architecture & Workflow
  • Git Installation & Configuration
  • Repository Operations: Clone, Commit, Push, Pull
  • Branching Strategies: GitFlow, Trunk-Based Development
  • Merging, Rebasing & Conflict Resolution
  • GitHub: Pull Requests, Code Reviews, Issues
  • Git Tags, Stash & Advanced Commands
  • Git Hooks & Pre-commit Automation
  • GitHub Actions Introduction
  • Using Copilot for Git Commands & Workflows
  • Continuous Integration Principles & Benefits
  • Continuous Delivery vs Continuous Deployment
  • CI/CD Pipeline Architecture & Stages
  • Build Automation & Artifact Management
  • Automated Testing in CI/CD (Unit, Integration, E2E)
  • Code Quality Gates & Static Analysis
  • Deployment Strategies: Blue-Green, Canary, Rolling
  • Pipeline as Code Concepts
  • CI/CD Security Considerations
  • Metrics & KPIs for CI/CD
  • Jenkins Architecture & Installation
  • Jenkins UI & Job Configuration
  • Freestyle vs Pipeline Jobs
  • Declarative Pipeline Syntax
  • Jenkinsfile & Pipeline as Code
  • Jenkins Plugins: Git, Maven, Docker, SonarQube
  • Distributed Builds & Jenkins Agents
  • Jenkins Security & Access Control
  • Jenkins Shared Libraries
  • Jenkins Integration with Cloud Platforms
  • GitHub Actions Architecture & Concepts
  • Workflow Syntax & Triggers
  • Jobs, Steps & Actions
  • Secrets & Environment Variables
  • Matrix Builds & Strategy
  • Caching & Artifacts
  • Reusable Workflows & Composite Actions
  • Self-Hosted Runners
  • GitHub Actions Marketplace
  • Security Best Practices for Actions
  • Introduction to Containerization & Benefits
  • Docker Architecture: Images, Containers, Registry
  • Docker Installation & Configuration
  • Docker Images: Building, Tagging, Pushing
  • Dockerfile Best Practices & Multi-Stage Builds
  • Container Lifecycle Management
  • Docker Networking: Bridge, Host, Overlay
  • Docker Volumes & Data Persistence
  • Container Resource Management
  • Docker Logging & Debugging
  • Docker Image Optimization Techniques
  • Docker Compose: Architecture & Syntax
  • Multi-Container Application Management
  • Docker Compose for Development & Testing
  • Docker Security: Image Scanning, Secrets
  • Vulnerability Scanning with Trivy
  • Docker Registry: Harbor, ECR, ACR
  • Docker in CI/CD Integration
  • Docker Buildx & Multi-Platform Images
  • Container Runtime Security
  • Kubernetes Architecture: Control Plane, Nodes
  • Kubernetes Objects: Pods, Services, Deployments
  • Kubernetes Installation: Minikube, kind, kubeadm
  • kubectl Commands & Operations
  • YAML Manifests for Kubernetes
  • ReplicaSets & Deployments
  • Services & Networking in Kubernetes
  • ConfigMaps & Secrets Management
  • Labels, Selectors & Annotations
  • Kubernetes Namespaces
  • StatefulSets & DaemonSets
  • Persistent Volumes & Persistent Volume Claims
  • Storage Classes & Dynamic Provisioning
  • Ingress Controllers & Ingress Rules (NGINX, Traefik)
  • Horizontal & Vertical Pod Autoscaling
  • Resource Quotas & Limits
  • Multi-Tenancy & Namespaces
  • Helm: Package Manager for Kubernetes
  • Helm Charts: Structure & Best Practices
  • Kubernetes RBAC & Security
  • Introduction to Infrastructure as Code
  • Terraform Architecture & Workflow
  • HCL (HashiCorp Configuration Language)
  • Terraform Providers (AWS, Azure, GCP)
  • Resources, Variables & Outputs
  • Terraform State Management
  • Remote State & Backend Configuration
  • Terraform Modules & Reusability
  • Terraform Workspaces for Environments
  • Terraform Cloud & Enterprise
  • Introduction to Configuration Management
  • Ansible Architecture: Control Node, Managed Nodes
  • Ansible Installation & Configuration
  • Inventory Management (Static & Dynamic)
  • Ad-hoc Commands
  • Ansible Playbooks: YAML Syntax
  • Ansible Modules & Collections
  • Variables, Facts & Conditionals
  • Ansible Roles & Galaxy
  • Ansible Vault for Secrets
  • Ansible Tower/AWX
  • AWS Cloud Fundamentals for DevOps
  • AWS CodePipeline: Architecture & Setup
  • AWS CodeBuild: Build Automation
  • AWS CodeDeploy: Deployment Strategies
  • AWS CodeCommit & CodeArtifact
  • EC2, VPC, S3, RDS for DevOps
  • AWS ECS & EKS: Container Orchestration
  • AWS Lambda & Serverless DevOps
  • AWS CloudFormation for IaC
  • AWS CloudWatch: Monitoring & Logging
  • AWS Systems Manager & Parameter Store
  • Introduction to Azure DevOps Services
  • Azure Pipelines Architecture (Classic vs YAML)
  • Multi-Stage Pipelines & Templates
  • Azure Repos, Boards & Test Plans
  • Azure Kubernetes Service (AKS) Deep Dive
  • Azure Container Instances (ACI)
  • Azure Functions & Serverless
  • Azure Resource Manager (ARM) Templates & Bicep
  • Azure Monitor & Application Insights
  • Azure Key Vault Integration
  • GitHub Copilot for Azure DevOps
  • Monitoring vs Observability: Three Pillars (Metrics, Logs, Traces)
  • Prometheus: Architecture & Installation
  • Metrics Collection & PromQL
  • Grafana: Dashboards & Visualizations
  • ELK Stack: Elasticsearch, Logstash, Kibana
  • Loki for Log Aggregation
  • Application Performance Monitoring (APM)
  • Distributed Tracing with Jaeger/Zipkin
  • Alerting & Incident Management
  • SLIs, SLOs, SLAs & Error Budgets
  • OpenTelemetry Overview
  • Introduction to DevSecOps & Shift-Left Security
  • Static Application Security Testing (SAST)
  • Dynamic Application Security Testing (DAST)
  • Software Composition Analysis (SCA)
  • Container Security Scanning (Trivy, Clair)
  • Infrastructure Security: CIS Benchmarks
  • Secrets Management: HashiCorp Vault, Azure Key Vault
  • Policy as Code: OPA, Kyverno
  • Security in CI/CD Pipelines
  • Compliance as Code
  • AI-Powered Security Analysis
  • Introduction to GitOps Principles
  • GitOps vs Traditional DevOps
  • ArgoCD: Architecture & Installation
  • Flux CD: Setup & Configuration
  • Declarative Infrastructure with GitOps
  • Application Sets & Multi-Cluster Management
  • Progressive Delivery: Canary, Blue-Green
  • Argo Rollouts for Advanced Deployments
  • Feature Flags & A/B Testing
  • Rollback Strategies & Self-Healing
  • GitOps Best Practices & Security
  • Introduction to AIOps: Concepts & Benefits
  • AIOps Platforms Overview (Dynatrace, Datadog, Splunk)
  • Machine Learning for IT Operations
  • Anomaly Detection in Monitoring
  • Predictive Analytics for System Failures
  • AI-Powered Log Analysis & Pattern Recognition
  • Intelligent Alerting & Noise Reduction
  • Root Cause Analysis with AI
  • Automated Incident Triage & Response
  • Capacity Planning with ML
  • AIOps Integration with Existing Tools
  • AI in Software Engineering: Overview & Trends
  • AI Coding Assistants: Copilot, CodeWhisperer, Tabnine
  • AI-Powered Code Review & Analysis
  • Automated Test Generation with AI
  • AI for Code Refactoring & Optimization
  • Natural Language to Code Conversion
  • AI-Powered Documentation Generation
  • Code Security Analysis with AI
  • AI for Bug Detection & Resolution
  • ChatOps & Conversational AI for DevOps
  • Building AI-Enhanced CI/CD Pipelines
  • Generative AI in DevOps: Advanced Use Cases
  • LLMs for Infrastructure Code Generation
  • AI Agents for DevOps Automation
  • Custom GPT/Claude for DevOps Tasks
  • Platform Engineering & Internal Developer Platforms (IDP)
  • Self-Service Infrastructure Portals (Backstage)
  • FinOps: AI-Driven Cost Optimization
  • Emerging Trends: WebAssembly, eBPF, Service Mesh
  • Building AI-Native DevOps Culture
  • Kubernetes Operators: Concepts & Use Cases
  • Custom Resource Definitions (CRDs)
  • Building Custom Operators with Operator SDK
  • Service Mesh Introduction: Why Service Mesh?
  • Istio Architecture: Control Plane & Data Plane
  • Istio Installation & Configuration
  • Traffic Management: Virtual Services, Destination Rules
  • mTLS & Security Policies
  • Observability with Istio: Kiali, Jaeger Integration
  • Linkerd Overview & Comparison
  • Multi-Cluster Service Mesh
  • Service Mesh Best Practices
  • Introduction to Chaos Engineering
  • Chaos Engineering Principles & Practices
  • Chaos Monkey & Netflix Simian Army
  • Chaos Toolkit & LitmusChaos
  • Gremlin for Enterprise Chaos
  • Designing Chaos Experiments
  • Site Reliability Engineering (SRE) Fundamentals
  • SRE vs DevOps: Complementary Practices
  • Service Level Indicators (SLIs)
  • Service Level Objectives (SLOs)
  • Error Budgets & Budget Policies
  • Incident Management & Postmortems
  • Toil Reduction Strategies
  • On-Call Best Practices
  • Advanced Terraform Patterns & Anti-Patterns
  • Terraform Functions & Expressions
  • Dynamic Blocks & For Each
  • Terragrunt: DRY Infrastructure Code
  • Terragrunt Configuration & Best Practices
  • Multi-Cloud Infrastructure Management
  • Terraform Cloud & Enterprise Features
  • Sentinel Policy as Code
  • Writing Sentinel Policies
  • Infrastructure Testing with Terratest
  • Terraform Import & State Surgery
  • Terraform CDK (CDKTF) Introduction
  • Pulumi Overview & Comparison
  • Cost Estimation with Infracost
  • Introduction to FinOps: Framework & Principles
  • FinOps Lifecycle: Inform, Optimize, Operate
  • Cloud Cost Fundamentals: Pricing Models
  • Reserved Instances & Savings Plans
  • Spot/Preemptible Instances Strategies
  • AWS Cost Explorer & Cost Anomaly Detection
  • Azure Cost Management & Budgets
  • Kubecost for Kubernetes Cost Management
  • Right-sizing Resources
  • Idle Resource Detection & Cleanup
  • Tagging Strategies for Cost Allocation
  • Showback & Chargeback Models
  • AI-Powered Cost Optimization
  • Cost Governance & Policies
  • Building FinOps Culture

Advanced DevOps Certification & Exam

To achieve the DevOps Engineer certification in San Juan, Puerto Rico, participants must attend all the virtual sessions, complete the required assessments, submit hands-on DevOps assignments, and successfully finish a final capstone project. The capstone requires building and automating a CI/CD pipeline, applying GitOps deployment practices, and integrating AI-driven improvements into DevOps processes.

Through this certification, learners in San Juan, Puerto Rico must demonstrate practical skills in CI/CD automation, Kubernetes management, infrastructure as code using Terraform and Ansible, and cloud platforms such as AWS and Azure. They are also expected to show an understanding of GitOps practices, AIOps concepts, and AI-supported DevOps workflows used in modern IT environments.

Why choose our Advanced DevOps Certification in San Juan, Puerto Rico?

Most Popular

Preferred by professionals preparing for the DevOps Engineer certification.

Convenient Schedule

We offer flexible scheduling options, including both weekday and weekend classes to suit the needs of working professionals.

Low Cost

Without compromising on quality, we have priced our DevOps certification training courses very competitively. We guarantee that you will find us more economical than any other training provider.

Unmatched Quality

We, along with our affiliate partners, are dedicated to creating high-quality study materials and delivering an exceptional learner experience. All content adheres to strict quality standards to ensure accuracy and reliability.

Course Design

Backed by years of experience in professional training, our courses are designed not only to help you prepare to be a DevOps Engineer, but also to equip you with real-world best practices.
 

Trainers

All our trainers are certified professionals with deep expertise in various industry-standard frameworks. They bring over a decade of experience in both consulting and training, and are passionate about sharing their knowledge to help professionals advance their careers.

Never miss a class

If you miss a session for any reason, you can either attend the same session in another live batch (subject to availability) or watch the recorded session in the LMS at your convenience.

Lifetime Access

Enjoy lifetime access to our Learning Management System (LMS), where you can revisit class recordings and presentations anytime online.

Customer Satisfaction

We’re here 24/7 to ensure you’re heard and supported, no matter what questions or doubts you may have. Our team is committed to delivering exceptional customer service to every individual and organization we serve.

Advanced DevOps Training Frequently Asked Questions

The Advanced DevOps Certification with Generative AI course is designed to help you master modern DevOps practices while integrating Generative AI into real-world software delivery workflows.

The program covers the complete DevOps lifecycle, including version control, continuous integration, continuous delivery, containerization, Kubernetes orchestration, Infrastructure as Code, cloud deployments, GitOps practices, monitoring, and AIOps. In addition, it introduces how Generative AI can be applied to automate scripting, optimize CI/CD pipelines, enhance testing, improve observability, and accelerate incident response.

Through hands-on projects and practical implementations, you will gain experience building scalable, cloud-native DevOps environments and intelligent automation pipelines aligned with current industry demands.

By the end of the course, you will be equipped with in-demand DevOps and AI-driven automation skills required to design, deploy, and manage production-ready systems.

Take the next step in your DevOps career. Enroll now to master advanced DevOps practices with Generative AI and become job-ready for modern cloud and automation roles.
 

Upon completing the Advanced DevOps certification with Generative AI training, you’ll be equipped to pursue roles such as:

  • DevOps Engineer
  • Site Reliability Engineer (SRE)
  • Cloud Infrastructure Engineer
  • DevOps Automation Specialist
  • AI-Enabled DevOps Consultant

These roles are in high demand across organizations adopting cloud-native architectures and automated DevOps practices enhanced by AI.

You will develop the following skills through this DevOps Engineer certification course with Generative AI training:

  • CI/CD Pipeline Design & Automation: Build, optimize, and manage scalable continuous integration and delivery workflows.

  • Containerization & Orchestration: Deploy and manage applications using Docker and Kubernetes.

  • Infrastructure as Code (IaC): Automate infrastructure provisioning and configuration with Terraform and Ansible.

  • Cloud DevOps Practices: Design and manage cloud-native deployments on AWS and Azure.

  • GitOps & Version Control: Implement automated, declarative deployment strategies using Git-based workflows.

  • Monitoring, Logging & AIOps: Strengthen observability with intelligent monitoring and AI-driven insights.

  • Generative AI in DevOps: Use AI to enhance code quality, automate testing, optimize deployments, and improve incident response.

  • Hands-On Project Experience: Apply your knowledge through real-world, production-oriented DevOps scenarios.

By the end of the course, you will be able to confidently design, automate, and manage intelligent, production-ready DevOps pipelines in enterprise environments.

Ready to become a job-ready DevOps Engineer? Enroll now to master in-demand DevOps and Generative AI skills and accelerate your career in modern cloud and automation roles.

Generative AI is integrated into this DevOps certification course to enhance productivity, automation, and intelligent decision-making across the DevOps lifecycle. As covered in the program, you will learn how to:

  • Leverage AI for Code & Script Generation: Use Generative AI tools to create configuration files, pipeline scripts, and infrastructure templates more efficiently.
  • Enhance CI/CD Pipelines with AI: Improve build and deployment workflows through AI-assisted optimization, error detection, and automation.
  • Automate Testing with AI: Generate test cases, improve test coverage, and streamline validation processes.
  • Support Infrastructure as Code (IaC): Accelerate Terraform and Ansible template creation with AI-driven recommendations.
  • Implement AI-Powered Monitoring (AIOps): Analyze logs and metrics intelligently to detect anomalies and predict potential failures.
  • Accelerate Incident Management: Use AI to summarize logs, identify root causes, and recommend remediation steps.
  • Automate Documentation & Knowledge Sharing: Generate runbooks, deployment documentation, and technical summaries automatically.

By embedding Generative AI into core DevOps practices, the course enables you to build faster, smarter, and more resilient DevOps pipelines aligned with modern industry needs.

Yes, we do offer additional discounts to group and corporate training customers. Please email us at [email protected] to find out more about our group discount offerings.

Use the "Submit your query"section in this page or check "Contact Us" section. Alternatively, please send an email to [email protected] to find out more about our course offerings.

If you're unemployed right now, or you're a student taking this course for career growth, we do provide additional discounts for you on selected courses. Please email [email protected] to avail this benefit and discount coupon.

Note: These discounts are available on selected courses only.

We do not offer placement or placement assistance services at this time. However, our training is designed to equip you with in-demand skills, hands-on experience, and certification readiness to help you confidently pursue new career opportunities. Many of our learners have successfully transitioned into new roles or advanced in their careers based on the knowledge and certifications gained throughĀ ourĀ programs

San Juan, Puerto Rico

Advanced DevOps Certification Training Course with Gen AI in San Juan, Puerto Rico

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