Comprehensive AWS Cloud Engineering Course Overview

Comprehensive AWS Cloud Engineering Course Overview

Unlock your potential with Koenig Solutions' Comprehensive AWS Cloud Engineering course, a 26-hour deep dive into Amazon Web Services (AWS). This course covers everything from Cloud Computing basics to advanced topics like AWS DevOps Tools and AI & ML with SageMaker. Gain hands-on experience with labs on IAM, VPC, EC2, S3, and more. By the end of this course, you'll be proficient in designing, deploying, and managing AWS infrastructure, ready to tackle real-world challenges. Perfect for IT professionals looking to enhance their AWS expertise and achieve career growth. Join us and become a cloud engineering expert!

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Target Audience for Comprehensive AWS Cloud Engineering

The Comprehensive AWS Cloud Engineering course by Koenig Solutions offers an in-depth understanding of AWS services, designed to equip IT professionals with essential cloud engineering skills.


  • Cloud Engineers
  • Solutions Architects
  • System Administrators
  • DevOps Engineers
  • Network Engineers
  • IT Managers
  • Database Administrators
  • Software Developers
  • Data Engineers
  • Machine Learning Engineers
  • AI Specialists
  • IT Consultants
  • Technical Leads


Learning Objectives - What you will Learn in this Comprehensive AWS Cloud Engineering?

Comprehensive AWS Cloud Engineering Course Overview

This 26-hour Comprehensive AWS Cloud Engineering course covers essential AWS services and solutions, focusing on cloud infrastructure, IAM, networking, compute, storage, databases, monitoring, deployment, DevOps, data analytics, and AI/ML.

Learning Objectives and Outcomes

Upon completing this course, participants will be able to:

  • Understand the fundamentals of AWS and cloud computing.
  • Implement and manage AWS Identity and Access Management (IAM) users, roles, and policies.
  • Design and deploy secure and scalable VPC-based network architectures.
  • Launch and manage EC2 instances and implement serverless computing with AWS Lambda.
  • Utilize Amazon S3 for various storage needs, along with data migration tools.
  • Deploy and manage relational and NoSQL database solutions with Amazon RDS, Aurora, and DynamoDB.
  • Monitor AWS infrastructure using CloudWatch and CloudTrail, and implement elastic load balancing and auto-scaling.
  • Automate infrastructure deployment using AWS CloudFormation and manage resources with AWS Systems Manager.
  • Understand microservices and container services including Amazon ECR, ECS, EKS, and Fargate.
  • Implement continuous integration and deployment using AWS DevOps tools like CodePipeline.
  • Use AWS data analytics tools such as Kinesis, Athena, and

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