Edoxi’s comprehensive 24-40 hour online AWS DevOps Engineer training cultivates expertise in DevOps culture, AWS services, and infrastructure as code for high-velocity application delivery. This customizable corporate training focuses on designing, implementing, and managing robust AWS environments. The AWS DevOps Engineer training aligns with industry best practices and the DOP-C02 certification exam objectives.
Our AWS DevOps Engineer curriculum covers key areas such as DevOps best practices on AWS, autonomous team structures, and advanced deployment strategies like blue/green deployments. Participants gain proficiency in essential AWS services, including CloudFormation for infrastructure as code, CodeCommit for source control, CodeBuild for automated processing, and CodePipeline for CI/CD orchestration. The AWS DevOps Engineer training also delves into containerization with Docker, security integration within pipelines, and comprehensive monitoring using CloudWatch and X-Ray.
The AWS DevOps Engineer course is designed for DevOps Engineers, Operations Engineers, System Administrators, Software Developers, and other IT professionals seeking to specialise in AWS DevOps. Upon successful completion, you will receive Edoxi’s AWS DevOps Engineer course certificate. This credential shows that you’re prepared for the DOP-C02 exam and have the skills needed for roles like DevOps Engineer, Site Reliability Engineer, and Cloud Infrastructure Manager.
The AWS DevOps Engineer Professional (DOP-C02) exam validates your advanced skills in provisioning, operating, and managing distributed systems on AWS. It also measures your ability to implement CI/CD pipelines, automate security and governance, and manage monitoring and logging. Below are the key exam details:
| Exam Criteria | Details |
| Exam Code | DOP-C02 |
| Exam Name | AWS DevOps Engineer – Professional |
| Duration | 180 minutes |
| Number of Questions | 75, Multiple Choice and Multiple Response |
| Passing Score | 750/1000 |
| Fees | USD 300 (approximately AED 1,100) |
| Certification Validity | 3 Years |
| Exam Administration Authority | Pearson VUE |
Access fully configured AWS labs to implement CI/CD pipelines, deploy infrastructure, and practice with CodeDeploy and CodePipeline in a real cloud environment.
Access comprehensive study materials, guides, and documentation directly from AWS to support the learning journey and serve as future reference materials.
Participate in engaging presentations, collaborative group exercises, and instructor-led discussions that reinforce key DevOps concepts and methodologies.
Deploy reliable infrastructure using CloudFormation and implement blue/green deployments with Elastic Beanstalk.
Create and deploy applications using CodeDeploy and CodePipeline for automated workflows.
Build serverless workflows with Step Functions and Lambda for modern cloud applications.
Professionals responsible for implementing and managing CI/CD pipelines who want to leverage AWS services for DevOps practices.
IT operations staff looking to automate infrastructure provisioning and application deployment using AWS tools.
Sysadmins seeking to transition to cloud-based operations and implement Infrastructure as Code principles.
Coders interested in expanding their skills to include deployment automation and cloud service integration.
Individuals with basic AWS knowledge ready to specialise in DevOps methodologies and advanced AWS services.
Technology workers aiming to enhance their career prospects with in-demand AWS DevOps engineering skills.
Our online AWS DevOps Engineer course blends expert-led sessions with hands-on projects based on real-world DevOps scenarios. Key projects include
Create scalable infrastructure with CloudFormation templates, including networks, security groups, and application tiers for production environments.
Implement zero-downtime deployments using Elastic Beanstalk to manage parallel environments and seamless traffic switching between versions.
Configure automated deployment pipelines with CodeDeploy and CodePipeline to streamline application releases across development stages.
Build event-driven applications using Lambda functions orchestrated by Step Functions to create complex workflows without server management.
Establish end-to-end automation for code integration, testing, and deployment using AWS developer tools for reliable software delivery.
By completing our AWS DevOps Engineer course, you will build advanced technical skills and master essential AWS DevOps tools. You will also gain the confidence to design, implement, and manage robust cloud environments. Key outcomes include
Get expert assistance in getting your AWS DevOps Engineer Course customised!
Here’s a four-step guide to becoming a AWS DevOps Engineer professional.
Join Edoxi’s AWS DevOps Engineer Course
Among many options available, Edoxi is the best choice. Here’s why Edoxi’s AWS DevOps Engineer training is the perfect fit for your needs
Delivers AWS’s official DevOps Engineering curriculum with up-to-date, standardised content designed by AWS experts.
Provides extensive AWS labs using services like CodePipeline, CloudFormation, and ECS for practical learning.
Aligns fully with AWS DevOps Engineer – Professional exam - DOP-C02 - objectives and provides targeted practice questions.
Offers 1:1 student-teacher interaction for individualised attention and tailored learning support.
Choose between 3-day intensive or 5-day comprehensive training options to fit your needs.
Trusted by corporate clients across the Middle East and select African regions for Cloud training.
Our mentors are leaders and experts in their fields. They can challenge and guide you on your road to success!
Manish Rajpal
Manish is a passionate Corporate Trainer, AI Consultant, and Cloud Solutions Architect. He empowers clients across the globe to build and maintain highly available, resilient, scalable, and secure solutions, now with a growing emphasis on AI-powered architectures. With over 15,000 professionals trained, Manish specialises in technologies including Amazon Web Services, Microsoft Azure, Microsoft Copilot and GitHub Copilot and increasingly, AI and Machine Learning.
Manish has led research and workshops focused on integrating AI into cloud environments, exploring use cases like intelligent automation, natural language processing, and responsible AI practices.
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