Skip to main content

New on Cloud Academy, January ’18: Security, Machine Learning, Containers, and more


Introduction to Kubernetes

Kubernetes allows you to deploy and manage containers at scale. Created by Google, and now supported by Azure, AWS, and Docker, Kubernetes is the container orchestration platform of choice for many deployments. For teams deploying containerized applications, this learning path will serve as introduction to the Kubernetes ecosystem and a primer for preparing for production. You will work alongside us as we explore key features by deploying a sample application, and you will be able to practice deploying stateful and stateless applications in two hands-on labs.


Introduction to Azure Machine Learning Studio

Azure Machine Learning Studio is machine learning at its most accessible. With this web-based software, you can train and deploy machine learning models using a drag-and-drop interface, without any coding whatsoever. This course will help teams get started using Machine Learning Studio. You will learn how to prepare your data, train a machine learning model, and deploy it as a predictive web service across a series of hands-on demos.
Introduction to VMware Cloud on AWS

VMware Cloud on AWS allows you to seamlessly transition your VM workloads to the AWS cloud to take advantage of on-demand resourcing, scalability, flexibility, security and other benefits of the public cloud. With this course, business managers evaluating a hybrid cloud solution will be able to understand how VMware’s private on-premises architecture works with AWS and the benefits that this combination offers the enterprise.
Getting Started with Migrating to the Cloud

Now that you’ve decided to migrate to the cloud, it’s time to shift from theory to practice. This course features hands-on strategies, techniques, and best practices that teams can apply in migrating business applications to public cloud services. Your teams will get practical guidance for building your migration business case, moving up the maturity curve, creating your migration roadmap, and more.
An Overview of AWS Trusted Advisor

As your infrastructure grows, how can you make sure you’re deploying your resources in the best way while ensuring tight security and resiliency against failure? AWS Trusted Advisor recommends improvements across your account to help optimize and hone your environment based on AWS best practices. In this course, you’ll get the hands-on practice and actionable knowledge you need to start using AWS Trusted Advisor to improve your AWS infrastructure.


Azure Key Vault and Disk Encryption

Azure Key Vault is a service for managing and encrypting keys, secrets, and digital certificates that streamlines the key management process. With Key Vault, you can encrypt keys and secrets (authentication keys, .PFX files, passwords, and more) using keys protected by hardware security modules (HSMs). In this hands-on lab, you will use PowerShell to build the Azure Key Vault to store keys and secrets used to encrypt an Azure Virtual Machine.
Diagnose Cancer with an Amazon Machine Learning Classifier

Can a computer predict a diagnosis in a way that is faster and less expensive? Researchers and teams working with binary classification models will find an effective tool in Amazon Machine Learning Classifier. In this hands-on lab, you will use the service to train a model with medical data, evaluate the model’s performance, and use the model to make diagnoses for predictions in real time.
Using an MXNet Neural Network to Style Images

The AWS Deep Learning AMI has everything you need to start building an AI system. The MXNet deep learning framework on AWS supports training and deployment of neural networks on a variety of devices. In this hands-on lab, you will use the AWS Deep Learning AMI and a GPU instance to perform neural style transfers and examine performance and cost metrics in Amazon CloudWatch.
Serverless Web Development with Python for AWS

Cloud providers make it easy for software engineers to focus on writing their code without having to focus on the underlying server. For DevOps Engineers, Developers, or Site Reliability Engineers experimenting with serverless, AWS offers a variety of services for creating fully serverless applications. In this lab, you will practice serverless web development with Python by testing and deploying a multi-user to-do list application that uses the AWS Serverless Application Model, Amazon Cognito, and DynamoDB.
Manage Access to Azure with Role-Based Access Control

Limiting access to resources based on a user’s role is a simple way to ensure security within your environment. Microsoft Azure provides fine-grained role-based access control (RBAC) mechanisms to secure your resources. In this hands-on lab, you will follow the principle of least privilege for users as you manage access to Azure with RBAC. You will use Azure PowerShell to create a custom role, learn how to assign roles to users, and get tips on how to define your own custom roles.

Written by

Related Posts

— February 28, 2018

How to Develop Machine Learning Models in TensorFlow

Predictive analytics and automation—through AI and machine learning—are increasingly being integrated into enterprise applications to support decision making and address critical issues such as security and business intelligence. Public cloud platforms like AWS offer dedicated services ...

Read more
  • Amazon Machine Learning
  • AWS
  • AWS Labs
— January 30, 2018

Analyze CPU vs. GPU Performance for AWS Machine Learning

For teams training complex machine learning models, time and cost are important considerations. In the cloud, different instance types can be employed to reduce the time required to process data and train models.Graphics Processing Units (GPUs) offer a lot of advantages over CPUs when...

Read more
  • Amazon Machine Learning
  • AWS
— July 10, 2017

AWS Global Infrastructure: Availability Zones, Regions, Edge Locations, Regional Edge Caches

Amazon Web Services is a global public cloud provider, and as such, it has to have a global network of infrastructure to run and manage its many growing cloud services that support customers around the world. In this post, we'll take a look at the components that make up the AWS  Global...

Read more
  • Amazon Machine Learning