AWS Academy

This introductory course is intended for students who seek an overall understanding of cloud computing concepts, independent of specific technical roles. It provides a detailed overview of cloud concepts, AWS core services, security, architecture, pricing, and support.

AWS Academy Generative AI Foundations course offers an introduction to artificial intelligence with a particular emphasis on generative AI technologies. While providing a broad foundational understanding of AI and Machine Learning (ML), the curriculum delves deeper into the concepts of generative AI and its applications in cloud computing.

Students will explore the fundamental concepts, capabilities, principles, use cases and associated AWS services and tools of generative AI in the context of the AWS cloud.

This introductory course introduces students to the concepts and terminology of artificial intelligence (AI) and machine learning (ML). By the end of this course, students will be able to select and apply ML services to resolve business problems. They will also be able to label, build, train, and deploy a custom ML model. This course contains approximately 20 hours of content delivered through lectures, hands-on labs, and project work.

This course is designed to help students develop technical expertise in data center operations. Although this is a foundational course, students should possess a general knowledge of mechanical and electrical engineering concepts.

This course provides an overview of the fundamental concepts and skills required for the Engineering Operations Technician role in a Data Center environment. Students will learn about topics such as data center basics, data center physical infrastructure, electrical fundamentals, and data center batteries and generators.

This course is designed to help students gain a foundational knowledge of cybersecurity principles and services for cloud computing through a guided hands-on approach. This course includes demonstrations, instructional guides, and real-life scenarios.

This intermediate-level course will help students gain technical expertise in development with cloud technologies. It will also help them prepare for the AWS Certified Developer - Associate certification exam. Upon completion, students will be able to develop with the AWS SDK and identify best practices for building and deploying applications in the AWS Cloud. This course contains approximately 40 hours of content delivered through lectures and hands-on labs.  

We recommend that students take AWS Academy Cloud Foundations or equivalent before taking this course.

This intermediate-level course covers the fundamentals of building IT infrastructure on AWS and helps students gain the skills they need to pursue the AWS Certified Solutions Architect – Associate certification. This course contains approximately 40 hours of content delivered through lectures, hands-on labs, and project work.

We recommend that students take AWS Academy Cloud Foundations or equivalent before taking this course.

This intermediate-level course is designed for students who are pursuing careers that require machine learning knowledge. Students will learn how to describe the terms in the natural language processing (NLP) ecosystem; identify how to use NLP in business; and indicate the range of problems, tasks, and solutions with NLP.

AWS Academy Data Engineering is designed to help students learn about and get hands-on practice with the tasks, tools, and strategies used to collect, store, prepare, analyze, and visualize data for use in analytics and machine learning applications. Throughout the course, students will explore use cases from real world applications that will enable them to make informed decisions while building the data pipeline for their particular application.

Long-running hands-on lab environments where educators can bring their own assignments and invite their students to get experience using select AWS Services.

What can you do with AWS Academy Learner Lab?

• Create a class for your students
• Invite your students
• Assign your own projects
• View a student’s workspace
• View analytics including time and money spent
• Includes access to over 100 AWS services
• Available to all AWS Academy educators that complete the Getting started with AWS Academy course

AWS Academy Cloud Data Pipeline Builder

In this project, students are challenged to use AWS services to build a data analytics pipeline to analyze website clickstream data without step-by-step guidance. The pipeline must reflect the principles of the AWS Well-Architected Framework and be able to ingest, transform, analyze, and visualize data to produce meaningful insights for businesses to make informed decisions. Specific sections of the assignment are meant to challenge students on skills that they have acquired throughout the learning process.

AWS Academy Cloud Web Application Builder

In this project, students are challenged to use AWS services to design and deploy a database-backed web application in the AWS Cloud without step-by-step guidance. The architecture must reflect the principles of the AWS Well-Architected Framework and be highly available, scalable, high performing, and secure. Specific sections of the assignment are meant to challenge students on skills that they have acquired throughout the learning process.

AWS Academy Cloud Security Builder

In this lab project, students are challenged to use AWS services to secure various resources in the AWS Cloud. The lab project is divided into four phases, which are independent of each other. The architecture must reflect the principles of the AWS Well-Architected Framework and the principle of least privilege. Specific sections of the assignment are meant to challenge students on skills that they have acquired throughout the learning process.

AWS Academy Microservices and CICD Pipeline Builder

In this project, students are challenged to use AWS services to design and build a microservices and continuous integration and continuous development (CI/CD) solution. First, students break a monolith application into separate microservices, based on functionality and API endpoints. Then, they migrate the application to run on a container-based architecture, which provides the ability for the different components of the application to scale independently. Specific sections of the assignment are meant to challenge students on skills that they have acquired throughout the learning process.