AWS Cloud Skills

We’ve tailored our learning recommendations to meet the needs of five groups of learners. The suggested courses provide the level of skills and knowledge, based by profession, to make effective and responsible decisions in the AWS cloud.

• Beginner the suggested course introduces learners to the AWS cloud, terminology and provides a basic concepts overview
• Understanding Cloud as an operational requirement recommended for learners that require a high-level understanding of the technical features and benefits of AWS cloud
• Decision maker recommended for learners that require a high-level understanding of the technical features and benefits of AWS cloud
• Financial decision maker recommended upskilling on cost optimisation and FinOps Pillars for the AWS cloud to make effective and responsible decisions
• Data specialist learn how to design, build, secure, and maintain analytics solutions
• Digital and technology professional role based training at associate level, specialty, or professional level

I am new to cloud and looking to understand the basics.

Start with the 

• AWS Foundations: Getting Started with the AWS Cloud Essentials  (1 hour) This course can help you build and validate an overall understanding of the AWS Cloud, key terminology, and help advance your AWS Cloud skills

Then progress to:

• AWS Cloud Practitioner Essentials (4 hours) if you seek an overall understanding of AWS Cloud or wish to complete your first AWS certification

Start with:

• AWS Technical Essentials (4 hours) Learn the fundamentals of identifying AWS services to make informed decisions about IT solutions based on your business requirements. Want to dive deeper? Head over to AWS Essentials for further details

Then progress to:

• AWS Cloud Quest: Cloud Practitioner (12 hours) is a role playing learning game that helps you develop practical cloud skills through interactive learning and hands on activities using AWS services. Complete all your assignments to earn your digital badge
• Cloud Essentials Knowledge Badge Readiness Path (7 hours) Learn foundational cloud concepts, AWS services, security, architecture, pricing, and support. This learning path presents domain
•  specific content and includes courses, knowledge checks, and a knowledge badge assessment. This path is a guide and presents learning in a structured order, it can be used as presented or you can select the content that is most beneficial
• AWS Cloud Practitioner Certification Prep (4.5 hours)

Learn how to design, build, secure, and maintain analytics solutions. You'll also learn the fastest way to get answers to your users' questions from your data.

Start with:

• Fundamentals of Analytics on AWS Part 1 (2 hours) This course is the first of two offerings designed to introduce learners to the current market trends in analytics. You will learn fundamental concepts such as types of analytics, the 5 V’s of big data, and the challenges associated with processing high volumes of data. This course also maps the 5 V’s of big data to AWS services for analytics
• Fundamentals of Analytics on AWS Part 2 (1.5 hours) Building upon the concepts introduced in Part 1, this course introduces learners to an overview of data lakes, data warehouses, and modern data architectures on AWS. You will learn about which AWS services can be used to build a data warehouse, data lakes, and modern data architectures on AWS. You will also see common modern data architecture use cases and a reference architecture

Then progress to:

• Data Analytics learning plan  This learning plan is designed to help developers, data analysts, and data engineers design, build, secure, and maintain analytics solutions. The digital training included in this learning plan will expose you to the fastest way to get answers from all your data to all your users. (Also available with Labs*)
• standard exam prep plan AWS Certified Data Engineer Associate (17 hours)

Learn about AWS' relational and nonrelational database services and how to choose which database is the best choice for your solution.

Start with:

• AWS Database Offerings (4 hours) this course provides a basic overview of different database technologies and architectures and introduces you to the various Amazon Web Services (AWS) database services. The course also covers the concept of the purpose-built database, which changes the one-size-fits-all methodology that previously existed
• Introduction to Building with AWS Databases (3 hours) this course explores the various databases that Amazon Web Services (AWS) offers and helps you understand how each of them solve unique business problems. It introduces you to AWS recommended best practices when designing solutions with AWS databases, and common tools for data migration

Then progress to the learning plan that is most relevant

• NoSQL Foundation learning plan (11 hours) Learn fundamentals of managed non-relational (no SQL) database services. The digital training included in this learning plan will expose you to AWS nonrelational database services including Amazon DocumentDB, Amazon DynamoDB, Amazon ElastiCache, Amazon Neptune, and Amazon QLDB
• Database learning plan: AWS Relational Database Services (23 hours) The digital training included in this learning plan will expose you to AWS relational database services including Amazon Relational Database Service (Amazon RDS), Amazon Aurora, and Amazon Redshift. (Also available with Labs*)

I am looking to understand the benefits of adopting Cloud in my organisation. 

These courses help you build general cloud knowledge without going into too much technical detail.

• AWS Cloud Essentials for Business Leaders (2 hours) Learn the fundamental concepts of cloud computing and how a cloud strategy can help companies meet business objectives
• Machine Learning for Leaders (1.5 hours) Learn how machine learning can help your teams maximize project results and gain critical insight into your business or customer needs
• Generative AI for Executives (13 mins) This course provides a high-level picture of generative AI. Learners explore what generative AI is, how it can address executives’ concerns and challenges, and how it supports business growth

Start with:

• AWS Billing and Cost Management (20 minutes) Learn about the AWS Billing and Cost Management service, and the functionality it offers. You will learn about some of the features available to help you analyze your cloud spending, as well as some of the features available to help you manage cloud spending

Then progress to:

• AWS Cloud for Finance Professionals (17 hours) Discover Cloud Financial Management (CFM) best practices, including how to measure, optimise, and plan cloud usage. Learn how to report, monitor, and allocate your cloud costs. Gain technical and pricing model based cost optimisation strategies, find out how to forecast cloud costs, and learn about organisational and governance based best practices that help drive cost efficient usage of AWS

The Solutions Architect pathway will help you identify services, features and best practices to build and design resilient, secure, and highly available cloud-based solutions on the AWS Cloud.

Solutions architect Knowledge Badge Readiness Path (52 hours) Helps build knowledge on how to design applications and large distributed systems on AWS.  This learning path presents domain specific content and includes courses, knowledge checks, and a knowledge badge assessment.

Data scientists and developers can learn how to integrate machine learning (ML) and artificial intelligence (AI) into applications. You'll also learn the tools and techniques for data platform and data science to build ML applications.

We recommend that students have prior knowledge of data analytics on AWS

Generative Artificial Intelligence (GenAI) uses Foundational Models (FMs) to create new content and ideas, such as conversations, stories, images, videos, and music. Generative AI has the potential to transform how organizations accomplish their mission. The portfolio of GenAI services available on AWS enables organizations to reinvent their applications and create entirely new customer experiences that drives productivity, and transforms how customers achieve mission goals. 

Start with

• Introduction to Generative AI: Art of the Possible (1 hour) Introduces generative AI, use cases, risks and benefits. With the help of a content generation example, we illustrate the art of the possible
• Planning a Generative AI Project (1 hour) – Learn about the technical foundations and key terminology related to generative artificial intelligence (AI). You will explore the steps to planning a generative AI project, and evaluate the risks and benefits of using generative AI
• Building a Generative AI-Ready Organisation (1 hour) By the end of the course, you should be able to describe the key considerations for building a generative AI-ready organisation. You will be equipped with the tools and the knowledge to upskill employees and to infuse generative AI thinking in your workplace
• Amazon Bedrock – Getting Started (1 hour) Learn about the benefits, features, typical use cases, technical concepts, and cost of Amazon Bedrock. You will also review an architecture that uses Amazon Bedrock, along with other Amazon Web Services (AWS) offerings, to build a chatbot solution

Then progress to:

• Foundations of Prompt Engineering (4 hours) This course introduces the basics of prompt engineering, and progresses to advanced prompt techniques. You will also learn how to guard against prompt misuse and how to mitigate bias when interacting with FMs
• Building Language Models on AWS (5.5 hours) This course introduces experienced data scientists to the challenges of building language models and the different storage, ingestion, and training options to process a large text corpus. The course also discusses the challenges of deploying large models and customising foundational models for generative artificial intelligence (generative AI) tasks using Amazon SageMaker Jumpstart
• Building Generative AI Applications Using Amazon Bedrock (4 hours) This course is designed for data scientists and machine learning developers who are interested in building generative artificial intelligence (generative AI) applications using either the Amazon Bedrock API or LangChain integration. In this course, you will learn about the architecture patterns to build applications for key generative AI use cases

Data scientists and developers can learn how to integrate machine learning (ML) and artificial intelligence (AI) into applications. You'll also learn the tools and techniques for data platform and data science to build ML applications.

We recommend that students have prior knowledge of data analytics on AWS.

Start with:

• Machine Learning Essentials for Business and Technical Decision Makers (1.5 hours)
• AWS Foundations: Machine Learning Basics (30 mins) What is machine learning? How can machine learning solve business problems? When is it appropriate to use a machine learning model? What are the phases of a machine learning pipeline? In this course, you get an overview of the concepts, terminology, and processes of the exciting field of machine learning
• AWS Foundations: How Amazon SageMaker Can Help (30 minutes) Learn how Amazon SageMaker mitigates the core challenges of implementing a machine learning pipeline. In this course, you learn how SageMaker notebooks and instances help power your machine learning workloads and review the key Amazon SageMaker features

• Amazon Q Developer - Getting Started (30 minutes) Using Amazon Q Developer, an AI-powered productivity tool that generates code suggestions ranging from snippets to full functions in near real time, you can streamline your coding experience and reduce the amount of code you have to write to complete your tasks, increasing coding efficiency and productivity. Amazon Q Developer also scans your code for security issues from right within your editor

Then progress to

• Machine Learning learning plan (32 hours) The digital training included in this learning plan will expose you to the broadest and deepest set of machine learning services and supporting cloud infrastructure. This learning plan can also help prepare you for the AWS Certified Machine Learning Specialty certification exam. (Also available with Labs*)
• Exam Readiness: AWS Certified Machine Learning – Specialty (4 hours)

AWS is offering any NHS employee in England, Wales and Scotland access to free training and exam preparation to help you build cloud skills for a digital career. The NHS England Skills Accelerator offers participants access to AWS online digital courses as well as instructor led training which offers live virtual learning with AWS experts. The program also includes opportunities to work alongside AWS solutions architects and professional services teams to help launch digital innovations in the cloud.

Contact us 

If you are interested in learning more about the NHS England Skills Accelerator please contact [email protected].

If you need further support as an NHS organisations planning or migrating to use Cloud Services contact us using our feedback form for an introductory 30 minute conversation with a member of the team.

Or find our more about our community of practice (you will need a FutureNHS account to login).

AQSS training materials can be redeemed through VitalSource. You can access VitalSource by using your existing AWS login or set up a new account by clicking on the Create a VitalSource account. You will need to use the same email address you used to register on the AWS training portal