AWS Cloud Technology Professional Certificate (AWS)

Foundational technology context for the cloud — starting from zero technical knowledge. Covers how computers work, modern IT infrastructure, internet-connected networks (web servers, web applications, DNS, IT security), and the basics of Cloud Computing including public, private, and hybrid models, plus the role of APIs.

Build a highly available, scalable, and cost-effective application step-by-step on AWS. Make informed decisions about when and how to apply core AWS services for compute (EC2, Lambda, ECS), storage (S3, EBS), and databases (RDS, DynamoDB). Includes AWS shared responsibility model, IAM, and using AWS services to monitor and optimize cloud infrastructure.

Gain the knowledge and skills to troubleshoot cloud-related issues. Review AWS infrastructure, develop a troubleshooting mindset, and learn AWS Support methods. Troubleshoot scenarios across Amazon EC2, AWS Lambda, and Amazon VPC, and apply controls with Amazon S3, Amazon RDS, AWS IAM, and AWS Organizations.

Develop the soft skills essential to cloud consulting — critical thinking, analytical problem-solving, customer requirements gathering, solution design, project execution, and stakeholder management. Build professional relationships, establish a personal brand, plan skill development, and prepare resumes and interview techniques.

A comprehensive 13-module overview preparing learners for the AWS Certified Cloud Practitioner exam. Covers the AWS Global Infrastructure, compute (EC2, Lambda, containers, Elastic Beanstalk), networking (VPC), storage, databases, AI/ML and data analytics on AWS, security, monitoring and governance, pricing and support, migration strategies, and the AWS Well-Architected Framework.

A thorough introduction to Python programming for AWS applications. Covers Python syntax, variables, functions, and packages; serverless architectures with AWS Lambda, Amazon API Gateway, and Cloud9; AWS databases with Amazon RDS and DynamoDB; and application integration services including Amazon SNS, SQS, and EventBridge — culminating in a hands-on Python and DynamoDB project.

Understand how software is built, tested, and deployed in modern teams. Define projects and apply project management best practices, then compare Waterfall, Agile, Scrum, and Kanban methodologies. Build a Continuous Integration / Continuous Delivery (CI/CD) pipeline using AWS CodeCommit, CodeBuild, CodeDeploy, and CodePipeline, with hands-on labs in Cloud9.

Simplify processes, enable agility and scalability, and deploy faster through cloud automation. Use the AWS CLI and Bash scripting for automation, apply Infrastructure as Code (IaC) with AWS CloudFormation, manage configuration as code, and use AWS Systems Manager and AWS Config for at-scale resource management.

Learn to think and act like a data analyst on AWS. Compare ETL and ELT approaches, explore data types, structures, and metadata, and contrast SQL and NoSQL databases. Apply AWS services for the ETL pipeline — Amazon API Gateway, AWS Lambda, Amazon RDS, Amazon DynamoDB, and Amazon QuickSight — labs.

A thorough review of the six pillars of the AWS Well-Architected Framework — Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability. Apply the framework to a real architecture, complete the capstone project document, and prepare for AWS Cloud Consultant interviews with a question bank.