Training Services

This course provides IT Security Professionals with the knowledge and skills needed to implement security controls, maintain an organization’s security posture, and identify and remediate security vulnerabilities. This course includes security for identity and access, platform protection, data and applications, and security operations.

This course teaches Network Engineers how to design, implement, and maintain Azure networking solutions. This course covers the process of designing, implementing, and managing core Azure networking infrastructure, Hybrid Networking connections, load balancing traffic, network routing, private access to Azure services, network security and monitoring. Learn how to design and implement a secure, reliable, network infrastructure in Azure and how to establish hybrid connectivity, routing, private access to Azure services, and monitoring in Azure.

This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. The course is not designed to teach students to become professional data scientists or software developers, but rather to build awareness of common AI workloads and the ability to identify Azure services to support them. The course is designed as a blended learning experience that combines instructor-led training with online materials on the Microsoft Learn platform (https://azure.com/learn). The hands-on exercises in the course are based on Learn modules, and students are encouraged to use the content on Learn as reference materials to reinforce what they learn in the class and to explore topics in more depth.

This course provides IT Identity and Access Professional, along with IT Security Professional, with the knowledge and skills needed to implement identity management solutions based on Microsoft Azure AD, and it connected identity technologies. This course includes identity content for Azure AD, enterprise application registration, conditional access, identity governance, and other identity tools.

In this course, the student will learn about the data engineering as it pertains to working with batch and real-time analytical solutions using Azure data platform technologies. Students will begin by understanding the core compute and storage technologies that are used to build an analytical solution. The students will learn how to interactively explore data stored in files in a data lake. They will learn the various ingestion techniques that can be used to load data using the Apache Spark capability found in Azure Synapse Analytics or Azure Databricks, or how to ingest using Azure Data Factory or Azure Synapse pipelines. The students will also learn the various ways they can transform the data using the same technologies that is used to ingest data. They will understand the importance of implementing security to ensure that the data is protected at rest or in transit. The student will then show how to create a real-time analytical system to create real-time analytical solutions.

Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure.

In this course, students will learn the fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build their foundational knowledge of cloud data services within Microsoft Azure. Students will identify and describe core data concepts such as relational, non-relational, big data, and analytics, and explore how this technology is implemented with Microsoft Azure. They will explore the roles, tasks, and responsibilities in the world of data. The students will explore relational data offerings, provisioning and deploying relational databases, and querying relational data through cloud data solutions with Microsoft Azure. They will explore non-relational data offerings, provisioning and deploying non-relational databases, and non-relational data stores with Microsoft Azure. Students will explore the processing options available for building data analytics solutions in Azure. They will explore Azure Synapse Analytics, Azure Databricks, and Azure HDInsight. Students will learn what Power BI is, including its building blocks and how they work together.

Azure Databricks is a cloud-scale platform for data analytics and machine learning. In this one-day course, you'll learn how to use Azure Databricks to explore, prepare, and model data; and integrate Databricks machine learning processes with Azure Machine Learning.

This course is for individuals who seek an overall understanding of the Amazon Web Services (AWS) Cloud, independent of specific technical roles. You’ll learn about AWS Cloud concepts, AWS services, security, architecture, pricing, and support to build your AWS Cloud knowledge. This course also helps you prepare for the AWS Certified Cloud Practitioner exam.

This course is for business leaders who seek an overall understanding of the fundamental concepts of cloud computing. Learn how a cloud strategy can help you meet business objectives. The course dives into the business value of the cloud through customer examples, exploring industry trends, and the Cloud Value Framework, which helps you understand the business value of building on AWS by assessing cost and value impact.

This course is for business leaders who seek an overall understanding of the fundamental concepts of cloud computing. Learn how a cloud strategy can help you meet business objectives. In this half-day, instructor-led course, you’ll explore the possibilities of cloud computing in banking, insurance, capital markets, payments, and financial technology. The course dives into the business value of the cloud through customer examples, exploring industry trends, and the Cloud Value Framework, which helps you understand the business value of building on AWS by assessing cost and value impact.

In this introductory course, you will learn about AWS products, services, and common solutions. You will learn the fundamentals of identifying AWS services so that you can make informed decisions about IT solutions based on your business requirements.

In this course, you will learn how to use the AWS SDK to develop secure and scalable cloud applications. We will explore how to interact with AWS using code and discuss key concepts, best practices, and troubleshooting tips.

This three-day course covers advanced development topics such as architecting for a cloud-native environment and deconstructing on-premises legacy applications and repackaging them into cloud-based, cloud-native architectures. It also covers how to apply the tenets of the Twelve-Factor Application methodology.

DevOps Engineering on AWS teaches you how to use the combination of DevOps cultural philosophies, practices, and tools to increase your organization’s ability to develop, deliver, and maintain applications and services at high velocity on AWS. This course covers continuous integration (CI), continuous delivery (CD), infrastructure as code, microservices, monitoring and logging, and communication and collaboration. Hands-on labs give you experience building and deploying AWS CloudFormation templates and CI/CD pipelines that build and deploy applications on Amazon Elastic Compute Cloud (Amazon EC2), serverless applications, and container-based applications. Labs for multi-pipeline workflows and pipelines that deploy to multiple environments are also included.

In this one-day course, you'll learn cloud-based deep learning solutions on the AWS platform. You'll learn how to run your models on the cloud using Amazon EC2‒based deep learning Amazon Machine Image (AMI) and Apache MXNet on AWS frameworks. In addition, you'll learn how to use Amazon SageMaker and deploy your deep learning models using AWS services like AWS Lambda and Amazon Elastic Container Service (Amazon ECS), all while designing intelligent systems on AWS.

Learn about various cloud migration strategies from an expert AWS instructor and how to apply each step of the migration process, including portfolio discovery, application migration planning and design, conducting a migration, and post-migration validation and application optimization. Practical labs reinforce learning, and each lab is designed to provide you with the understanding and foundation necessary to complete migration tasks in your organization.

This course teaches systems operators and anyone performing system operations functions how to install, configure, automate, monitor, secure, maintain, and troubleshoot the services, networks, and systems on AWS necessary to support business applications. The course also covers specific AWS features, tools, and best practices related to these functions.

Through a series of use case scenarios and practical learning, you’ll learn to identify services and features to build resilient, secure, and highly available IT solutions in the AWS Cloud. Expert AWS Instructors emphasize best practices using the AWS Well-Architected Framework and guide you through the process of designing optimal IT solutions, based on real-life scenarios. At the end of the course, you’ll practice building a solution and apply what you’ve learned with confidence.

Through a series of use case scenarios and practical learning, you'll explore AWS services that can be applied to solve architectural problems. You’ll find opportunities to combine your new knowledge with critical thinking and problem-solving skills. This course culminates in a final review project to reinforce what you’ve learned throughout the three days.