Securely Connecting AWS IoT Devices to the Cloud

AWS IoT Core provides secure, bidirectional communication between internet-connected devices, such as sensors, actuators, embedded microcontrollers, or smart appliances and the AWS Cloud.   In this course, you will learn how to securely connect a device to the cloud using AWS IoT Core, and ensure that an AWS IoT policy is properly set up to […]

AWS CloudTrail Lake Getting Started

In this course, you will learn the benefits and technical concepts of AWS CloudTrail Lake. Using CloudTrail Lake, you can aggregate, immutably store, and query Amazon Web Services (AWS) activities of management and data events recorded by AWS CloudTrail. You can use these events for auditing, security investigations, and operational troubleshooting purposes. CloudTrail Lake simplifies analysis workflows by integrating collection, storage, preparation, and optimization for analysis and querying within the same product. In this course, you will also review the basics of CloudTrail Lake and the business and technical challenges it can solve. Course level: Fundamental Duration: 60 minutes Activities This course includes presentations, demonstrations, and knowledge checks. Course objectives In this course, you will learn to: Learn how CloudTrail Lake works. Recognize the benefits of CloudTrail Lake. Explain the cost structure of CloudTrail Lake. Familiarize yourself with the technical concepts of CloudTrail Lake. List typical use cases for CloudTrail Lake. Specify what it would take to implement CloudTrail Lake in a real-world scenario. Explore how to use CloudTrail Lake on the AWS Management Console and use the AWS Command Line Interface (AWS CLI). Intended audience This course is intended for: AWS customers, Partners, and internal resources that want to understand how CloudTrail Lake can help them operate AWS solutions at scale. Prerequisites We recommend that attendees of this course have: A basic understanding of AWS offerings and the challenges that organizations face when operating Completed the Getting Started with AWS CloudTrail course Course outline Section 1: For Students Lesson 1: How to Use This Course Section 2: Introduction Lesson 2: Introduction to CloudTrail Lake Lesson 3: Architecture and Use Cases Section 3: Using AWS CloudTrail Lesson 4: How Do I Create an Event Data Store for CloudTrail Lake Events? Lesson 5: How Do I Use CloudTrail Lake to Configure Items? Lesson 6: How Do I Create an Event Data Store for Events Outside of AWS? Lesson 7 How Do I Query an Event Data Store? Lesson 8: How Do I Create and Delete an Event Data Store Using AWS CLI? Lesson 9: How Do I Delete Resources? Section 4: Resources Lesson 10: Learn More Lesson 11: Feedback

Fundamentals of Analytics on AWS – Part 2

This course is the second of two offerings designed to introduce learners to the current market trends in analytics. 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. Course level: Fundamental Duration: 1 hour 30 minutes Activities This course includes: lessons, videos, scenarios, and knowledge check questions. Course objectives In this course, you will learn to: Explain data lakes, benefits, and functions. Describe the basic data lake architecture, the AWS services used to build a data lake, and challenges with building a data lake. Explain AWS Lake Formation architecture, features and benefits. Explain data warehousing, challenges with an on-premises data warehouse, and available AWS solutions. Explain modern data architecture pillars and modern data architecture concepts. Explain data movement scenarios. Describe the data mesh architecture pattern, benefits, and available AWS solutions. Identify the available AWS services for building modern data architectures. Identify the components of modern data architecture. Describe common use cases for modern data architecture. Intended audience This course is intended for: Cloud architects Data engineers Data analysts Data scientists Developers Prerequisites We recommend that attendees of this course have: Reviewed AWS Cloud Practitioner Essentials or equivalent Completed Fundamentals of Analytics on AWS – Part 1 Course outline Section 1: Introduction Lesson 1: How to Use This Course Lesson 2: Course Overview Section 2: Architectures Lesson 3: Introduction to Data Lakes Lesson 4: Introduction to Data Warehousing Lesson 5: Introduction to Modern Data Architecture Lesson 6: AWS Services for Modern Data Architecture Section 3: Common Use Cases and Reference Architectures Lesson 7: Common Use Cases Lesson 8: Reference Architectures Section 4: Conclusion Lesson 9: Quiz Lesson 10: Course Summary Lesson 11: Appendix of Resources Lesson 12: Feedback

Fundamentals of Analytics on AWS – Part 1

This course is the first of two offerings designed to introduce learners to the current market trends in analytics. In Part 1, 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 and discusses how AWS provides the most comprehensive services on the market. Following completion of this course, learners are encouraged to continue their journey with Fundamentals of Analytics on AWS – Part 2 . Course level: Fundamental Duration: 2 hours Activities This course includes: lessons, videos, scenarios, and knowledge check questions. Course objectives In this course, you will learn to: Explain data analytics, data analysis, analytics types, techniques, and analytics challenges. Define machine learning (ML), ML on AWS, and different levels of AWS for ML services. Define the 5 V’s of big data. Explain common ways to store data, challenges, characteristics of source data storage systems, and available AWS solutions. Explain data transportation, options for different environments, and available AWS solutions. Define data processing, options for each type of processing, and available AWS solutions. Identify different types of data structures, types of data storage, and available AWS solutions. Explain where ETL and ELT fits in multiple places of the analytics pipeline, the elements of an ETL and ELT process, and available AWS solutions. Explain the use of business intelligence tools to gain value from analytics, and available AWS solutions. Intended audience This course is intended for: Cloud architects Data engineers Data analysts Data scientists Developers Prerequisites We recommend that attendees of this course have: Reviewed AWS Cloud Practitioner Essentials or equivalent Course outline Section 1: Introduction Lesson 1: How to Use This Course Lesson 2: Course Overview Section 2: Analytics Concepts Lesson 3: Analytics Lesson 4: Machine Learning Lesson 5: 5 Vs of Big Data Lesson 6: Volume Lesson 7: Variety Lesson 8: Velocity Lesson 9: Veracity Lesson 10: Value Section 3: AWS Services for Analytics Lesson 11: AWS Services for Volume Lesson 12: AWS Services for Variety Lesson 13: AWS Services for Velocity Lesson 14: AWS Services for Veracity Lesson 15: AWS Services for Value Section 4: Conclusion Lesson 16: Quiz Lesson 17: Course Summary Lesson 18: Appendix of Resources Lesson 19: Feedback

AWS Mainframe Modernization Replatform with Micro Focus Getting Started

AWS Mainframe Modernization Replatform with Micro Focus transforms legacy mainframe business applications. Businesses can scale their systems and procedures while enhancing their flexibility and agility. The tools also streamline the replatforming process while minimizing disruptions to operations. Course level: Fundamental Duration: 60 minutes Activities This course includes architecture overview and demonstrations. Course objectives In this course, you will learn to do the following: Understand the functionality and key components of AWS Replatform with Micro Focus Understand how AWS Replatform with Micro Focus works. Explain technical architecture and key use cases of AWS Replatform with Micro Focus. Examine the cost structure of AWS Replatform with Micro Focus. Intended audience This course is intended for the following job roles: Mainframe practitioners and specialists Mainframe developers Solution architects Prerequisites We recommend that attendees of this course have the following prerequisites: A minimum of 2 years of mainframe development, administration, and architecture experience Course outline Section 1: Introduction Module 1: Introduction to AWS Mainframe Modernization Replatform with Micro Focus Module 2: Architecture and Use Cases Section 2: Using AWS Mainframe Modernization Replatform with Micro Focus Module 3: How Can I Create Runtime and Deploy an Application? Module 4: How Do I Verify an Application Using a TN3270 Emulator? Module 5: How Do I Delete My Environment? Section 3: Resources Module 6: Learn More Module 7: Contact Us

Amazon CloudWatch Getting Started

In this course, you will learn the benefits and technical concepts of Amazon CloudWatch. Using CloudWatch, developers and operators can improve the performance and availability of their applications. CloudWatch helps you observe and monitor resources and applications in AWS Cloud, hybrid, or on-premises environments. In this course, you will also review the basics of CloudWatch, including the business and technical challenges it can solve. – Course level: Fundamental – Duration: 1 hour Activities This course includes presentations, demonstrations, and knowledge checks. Course objectives In this course, you will learn to: – Understand the basic technical concepts of CloudWatch. – Understand both the business and technical challenges of CloudWatch. – Create alarms, explore metrics, and monitor availability using synthetics. Intended audience This course is intended for: – Amazon Web Services (AWS) customers, partners, and internal resources who wish to better understand how CloudWatch can help them operate AWS solutions at scale Prerequisites We recommend that attendees of this course have: – A basic understanding of AWS offerings and the challenges that organizations face when operating Course outline Lesson 1: Introduction to CloudWatch Lesson 2: Architecture and Use Cases Lesson 3: How Do You Explore and Graph Default CloudWatch Metrics? Lesson 4: How Do You Explore and Graph Apache Logs in CloudWatch Logs? Lesson 5: How Do You Create CloudWatch Alarms? Lesson 6: How Do You Use CloudWatch Synthetics?

AWS Skill Builder Learner Guide

This course covers basic AWS Skill Builder navigation, content types, and helpful tips as you begin your learning journey. You will quickly learn how to use AWS Skill Builder and the other resources to supplement your learning. AWS Training and Certification regularly updates this course to reflect user interface changes and new features or content types. Course level: Fundamental Duration: 15 minutes Activities This course includes presentations. Course objectives In this course, you will learn to: Navigate AWS Skill Builder Intended audience This course is intended for: All AWS Skill Builder users Prerequisites We recommend that attendees of this course have: No prerequisites are needed Course outline Module 1: Learner Dashboard Module 2: Course Catalog – Individual Courses Module 3: Learning Plans Module 4: Subscription Content Module 5: Helpful Tips

AWS Glue Getting Started

Course description AWS Glue is a serverless data integration service that you can use to discover, prepare, and combine data for analytics, machine learning, and application development. In this course, you will learn the benefits, typical use cases, and technical concepts of AWS Glue, including AWS Glue Studio and AWS Glue DataBrew. DataBrew is a new visual data preparation tool that helps data analysts and data scientists clean and normalize data to prepare it for analytics and machine learning. You will have an opportunity to try the service through a demonstration using the AWS Management Console. • Course level: Fundamental • Duration: 2 hour¬¬s Activities This course includes presentations, graphics, and a demonstration with the option to follow along. Course objectives In this course, you will learn to: • Understand how AWS Glue works. • Familiarize yourself with the technical concepts of AWS Glue and DataBrew. • List typical use cases for AWS Glue and DataBrew. • Specify what it would take to implement AWS Glue and DataBrew in a real-world scenario. • Recognize the benefits of AWS Glue and DataBrew. • Explain the cost structure of AWS Glue. • Show how to use AWS Glue and DataBrew from the AWS Management Console. Intended audience This course is intended for the following roles: • Developers • Solutions architects • Data engineers • Business analysts Prerequisites AWS Technical Essentials Course outline • AWS Glue Basics o What does AWS Glue do? o What problems does AWS Glue solve? o What are the benefits of AWS Glue? o What is the data integration engine supported by AWS Glue? o How is AWS Glue used to architect a cloud solution? o What are typical use cases for AWS Glue? o What else should I keep in mind when using AWS Glue? • AWS Glue Cost Structure o How much does AWS cost? • Using AWS Glue Catalog and Glue Studio o What are the basic technical concepts I should know about AWS Glue Studio? o How do I crawl, catalog, and perform ETL on my data using AWS Glue? o Glue Studio tutorial video • AWS Glue DataBrew Basics o What are the basic technical concepts I should know about AWS Glue DataBrew? • Using AWS Glue DataBrew Data Profiling and Data Quality Checks o How do I profile my data, detect PII, and transform my data using AWS Glue DataBrew? o AWS Glue DataBrew tutorial video • Learn More o How can I learn more about AWS Glue?

Amazon EMR Getting Started

Course Description Amazon EMR is the industry-leading cloud big data solution for petabyte-scale data processing, interactive analytics, and machine learning using open-source frameworks such as Apache Spark, Apache Hive, and Presto. You can use Amazon EMR to set up, operate, and scale your big data environments and automate time-consuming tasks like provisioning capacity. In this course, you will learn Amazon EMR Serverless which is a new option in Amazon EMR that makes it efficient and cost-effective for data engineers and analysts to run applications built using open-source big data frameworks without having to tune, operate, optimize, secure, or manage clusters. Additionally, you will learn the benefits, typical use cases, and technical concepts of Amazon EMR. You will have an opportunity to try Amazon EMR Serverless and Amazon EMR Cluster through tutorials using the AWS Management Console. • Course level: Fundamental • Duration: 1 Hour Course objectives This course includes presentations, graphics, tutorials, and demonstrations with the option to follow along. Course objectives In this course, you will learn to: • Understand different deployment options available with Amazon EMR. • Understand how Amazon EMR works. • Understand the technical concepts of Amazon EMR Serverless. • List typical use cases for Amazon EMR Serverless. • Understand the technical concepts of Amazon EMR Cluster. • List typical use cases for Amazon EMR Cluster. • Specify what it would take to implement Amazon EMR in a real-world scenario. • Recognize the benefits of Amazon EMR. • Explain the cost structure of Amazon EMR. • Use Amazon EMR Serverless and Amazon EMR Cluster Intended audience This course is intended for: • Developers • Solutions architects • Data engineers • Data architects Prerequisites AWS Technical Essentials Data Analytics Fundamentals Course outline Introduction • Introduction to Amazon EMR • Amazon EMR Serverless Architecture and Use Cases • Amazon EMR Cluster Architecture and Use Cases Using Amazon EMR Serverless • How Do I Run a Spark Job on Amazon EMR Serverless? Using Amazon EMR • How Do I Create an Amazon EMR on EC2 Cluster? • How Do I Create an Amazon EMR Studio? • How Do I Create an Amazon EMR Workspace? • How Do I Run a Spark Job with Amazon EMR Studio Notebook? Resources • Learn More

AWS Organizations Getting Started

Course description In this course, you will learn the benefits and technical concepts of AWS Organizations. Using Organizations, you can manage accounts and consolidate billing capabilities so you can better meet the budgetary, security, and compliance needs of your organization. As an administrator of an organization, you can consolidate multiple Amazon Web Services (AWS) accounts and manage them centrally. In this course, you will also review the basics of Organizations and the business and technical challenges it can solve. ‐ Course level: Fundamental ‐ Duration: 1 hour Activities This course includes presentations, demonstrations, and knowledge checks. Course objectives In this course, you will learn to: ‐ Understand the basic technical concepts of Organizations. ‐ Understand both the business and technical challenges of organizations. ‐ Set up an organization. ‐ Manage invitations, services, and policies. ‐ View consolidated billing. Intended audience This course is intended for: ‐ AWS customers, partners, and internal resources who want to better understand how Organizations can help them operate AWS solutions at scale Prerequisites We recommend that attendees of this course have: ‐ A basic understanding of AWS offerings and the challenges that organizations face when operating them Course outline Lesson 1: Introduction to AWS Organizations Lesson 2: Architecture and Use Cases Lesson 3: How Do You Set Up Organizations in the AWS Management Console? Lesson 4: How Do You Manage an Organization? Lesson 5: How Do You View Consolidated Billing with an Organization? Lesson 6: How Do You Delete an AWS Organization? Lesson 7: How Do You AWS CLI with Organizations? Lesson 8: How Do You Use CloudFormation with Organizations?

Trails for AWS CloudTrail Getting Started

Course description In this course, you will learn the benefits and technical concepts of trails for AWS CloudTrail. Using trails for CloudTrail, you can archive, analyze, and respond to changes in your Amazon Web Services (AWS) resources. A trail is a configuration that helps deliver CloudTrail events to an Amazon Simple Storage Service (Amazon S3) bucket that you specify. In this course, you will also review the basics of trails for CloudTrail and the business and technical challenges it can solve. ‐ Course level: Fundamental ‐ Duration: 1 hour Activities This course includes presentations, demonstrations, and knowledge checks. Course objectives In this course, you will learn to: ‐ Understand the basic technical concepts of trails for CloudTrail. ‐ Understand both the business and technical challenges of trails for CloudTrail. ‐ Create a trail and query logs. Intended audience This course is intended for: AWS customers, partners, and internal resources who want to better understand how trails for CloudTrail can help them operate AWS solutions at scale. Prerequisites We recommend that attendees of this course have the following: ‐ A basic understanding of AWS offerings ‐ Completed the Getting Started with AWS CloudTrail course Course outline ‐ Introduction to Trails for CloudTrail ‐ Architecture and Use Cases ‐ How Do I Create a Trail in AWS CloudTrail in the AWS Management Console? ‐ How Do I Query AWS CloudTrail Logs? ‐ How Do I Use AWS CLI with Trails for CloudTrail? ‐ How Do I Delete Resources?

Choosing Serverless Containers for .NET

​In this course, you will learn how to choose the most suitable serverless container technology to run your .NET applications and workloads. Specifically, you will learn about the key features and benefits of AWS Fargate, AWS App Runner, and AWS Lambda.   •       Course level: Fundamental •       Duration: 1 hour   Activities This course includes the following: […]