Course Prerequisites
Prerequisites for Comprehensive AWS Cloud Engineering Course
To successfully undertake the Comprehensive AWS Cloud Engineering course, students should ideally have:
- Basic understanding of cloud computing concepts
- Familiarity with networking fundamentals
- Basic knowledge of at least one programming language (such as Python, Java, or any other)
- General understanding of IT infrastructure (servers, storage, and databases)
- Experience with command-line interfaces (CLI) would be beneficial but not necessary
These prerequisites ensure that students have a foundational understanding that will help them grasp the course content more effectively. Don't worry if you're not an expert in these areas—our course is designed to bring you up to speed!
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
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