AWS HPC Blog

Advancing research in the cloud: AWS announces expanded training resources

Advancing research in the cloud: AWS announces expanded training resources

Research leaders from academia, government, and non-profits consistently tell us that investing in researcher training is fundamental for accelerating scientific outcomes. In support of the diversity of researcher needs around the world, Amazon Web Services (AWS) is excited to announce three new researcher-focused learning plans and four ramp-up guides, which build upon our existing no-cost online AWS training pathways for researchers and research IT announced in 2020.

This expanded offering includes five additional courses that cater to different learning needs, including researchers who use AWS cloud for High Performance Computing (HPC), Quantum, Statistics, Artificial Intelligence (AI), Machine Learning (ML) and Generative Artificial Intelligence (Generative AI) in their daily research tasks. All courses for researchers can be found on our AWS ramp up guide home page.

Figure 1 - In support of the diversity of researcher needs around the world, AWS announcing three new researcher-focused learning plans and four ramp-up guides, building on our existing no-cost online AWS training pathways for researchers and research IT.

Figure 1 – In support of the diversity of researcher needs around the world, AWS announcing three new researcher-focused learning plans and four ramp-up guides, building on our existing no-cost online AWS training pathways for researchers and research IT.

Academic Research Learning Plans

Accelerate practical cloud skills and expertise with learning plans purposefully designed for researchers. Learning plans help you access learning that’s prescriptive, guided, and aligns with your objectives.

The new Academic Research Learning Plans build on the existing course, AWS Cloud Essentials for Business Leaders, which is suitable for decision-makers in academic research. Learn the fundamental concepts of cloud computing and how a cloud strategy can help entities in academic research and independent researchers meet business objectives. Explore how AWS brings the most advanced and secure cloud services, the deepest collaborative business solutions, and the fastest rate of innovation. With AWS, your organization can cloudify its business and create new efficiencies, differentiating and innovating at every stage of the journey.

The Foundational Researcher Learning Plan is for academic researchers and research professionals who want to become more proficient in optimizing research on AWS. It is suitable for academic researchers with a background of cloud architecting, DevOps, cloud administration, application development, data science, AI/ML, and ML processing. It is also suitable for researchers who want to build a comprehensive range of foundational knowledge and skills with AWS cloud. Learn how to use the right storage medium, remove heavy lifting with managed services, and reproduce research with containers and software-defined infrastructure. This learning plan can be completed in just over nine hours, and courses range in length from five minutes to three hours. There are eleven courses in this learning plan.

The Quantum Learning Plan is for academic researchers who need to learn Quantum Technologies at AWS, and who may have a background in database architecting, software development, IT management, data engineering, and database design. Learn how to program quantum computers and explore their potential applications. The Quantum learning plan contains two parts: Introduction to Building with AWS Databases (optional) and Amazon Braket – Knowledge Badge Readiness Path. This learning plan aims to help you build the fundamentals of choosing the right database to support your use case as well as offering a guided path that helps you build knowledge and technical skills to use Amazon Braket. Learners may also explore other Quantum content offered on AWS Skill Builder to supplement the learning plan.

Academic Research Ramp-up Guides

AWS Ramp-Up Guides offer a variety of resources to help you build your skills and knowledge of the AWS Cloud. Each guide features carefully selected digital training, classroom courses, videos, whitepapers, certifications, and more. AWS now offers four ramp-up guides that help academic researchers who use AI, ML, Generative AI, and HPC in their research activities, as well as the essential AWS knowledge for Statistician Researchers and Research IT professionals. The guides help learners decide where to start, and how to navigate, their learning journey. Some resources will be more relevant than others based on each learner’s specific research tasks.

AI, ML, Generative AI ramp-up guide (page 2) is for academic researchers who are exploring using AWS AI, ML, and Generative AI tools to improve efficiency and productivity in their research tasks. This course introduces seven components on AI and ML and ten components on Generative AI. The course starts with an introduction to AI, and covers AWS AI/ML services, such as Amazon SageMaker. The Generative AI content covers topics such as planning a Generative AI project, responsible AI Practices, security, compliance, and governance for AI solutions. The Generative AI topics also cover how to get started with Amazon Bedrock. Recommended prerequisites: basic understanding of Python.

High Performance Computing ramp-up guide (page 3) is designed for academic researchers who seek to use HPC on AWS. In this course, you will be introduced to eleven components that are essential about Higher Performance Computing on AWS. The course starts with an overview of HPC on AWS, followed by topics including AWS ParallelCluster and Research HPC Workloads on AWS Batch. Recommended prerequisites: complete AWS Cloud Essentials.

Statistician Researcher ramp-up guide (page 4) is specifically catered for researchers in the fields of statistics and quantum analysis. The course covers topics such as building with Amazon Redshift clusters, getting started with Amazon EMR, Machine Learning for Data Scientists, authoring visual analytics using Amazon QuickSight, Batch analytics on AWS, and Amazon Lightsail for Research. Recommended prerequisites: complete AWS Cloud Essentials.

Research IT ramp-up guide (page 5) is an extension of the Foundational Researcher Learning Plan, and enables Research IT leaders and professionals to dive deeper into specific topics. The goal of this extension for Research IT professionals is to dive deeper on fundamentals, understand management capabilities and implementing guardrails, cost optimization for research workloads, become familiar with platforms for research and research partners, and learn more about AWS Landing Zone and AWS Control Tower for Research. Recommended prerequisites: Foundational Researcher Learning Plan.

Accelerating your research computing on AWS

Researchers seek to push the envelope and see cloud as an instrument to further their research.

However, researcher cloud skills remain a barrier for a number of reasons, including limited organizational support for training.

Learn more about how institutions with cloud strategies turn to AWS to help them develop creative and scalable ways to address the cloud skills gap through upskilling and traditional academic settings on the AWS Research Computing webpage.

Maryclaire Abowd

Maryclaire Abowd

Maryclaire is a business development manager for worldwide public sector global education at Amazon Web Services (AWS). Maryclaire has over ten years of experience working in the IT and services industry for international government and education customers. Specializes in strategic content development, storytelling, customer journey mapping, digital transformation, international expansion, and qualitative research.

Shang Gao

Shang Gao

Dr. Shang Gao is a global lead for Academic Research at Amazon Web Services (AWS). Dr Gao has a PhD in the Economics for Education. Dr Gao is passionate about driving digital and business transformation, and help customers accelerate cloud and technology adoption for a better velocity of economic development and business innovation.