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 […]
Microsoft on AWS – Porting Assistant for .NET
Course description In this course, you will learn about Porting Assistant for .NET. This is an analysis tool that scans .NET Framework applications and generates a .NET core compatibility assessment, helping you port your applications to Linux faster. Porting Assistant for .NET quickly scans .NET Framework applications to identify incompatibilities with .NET Core, finds known replacements, and generates a detailed compatibility assessment. This reduces the manual effort involved in modernizing your applications to Linux. • Course level: Fundamental • Duration: 45 minutes Activities This course includes online materials, demonstrations, and knowledge check questions. Course objectives In this course, you will learn to do the following: • State the purpose of Porting Assistant for .NET. • Describe the benefits of moving from .NET Framework to .NET. • Describe the features of Porting Assistant for .NET. • List the prerequisites for running Porting Assistant for .NET. • State the steps involved in porting an application with Porting Assistant for .NET. • Identify how to contribute to the Porting Assistant for .NET tool. Intended audience This course is intended for the following roles: • Cloud architects • Cloud Practitioners • Developers Prerequisites We recommend that attendees of this course have: • A basic understanding of .NET Course outline Section 1: Overview • Lesson 1: How to Use This Course • Lesson 2: Introduction • Lesson 3: Reasons to Move from .NET Framework to .NET • Lesson 4: The Four Steps of Using Porting Assistant for .NET • Lesson 5: Features and Prerequisites • Lesson 6: How to Use Porting Assistant for .NET • Lesson 7: How to Interpret Porting Assistant for .NET Section 2: Conclusion • Lesson 8: Recap and Review • Lesson 9: Additional Resources • Lesson 10: Assessment • Lesson 11: Contact Us
Amazon Kendra Getting Started
Course description: Amazon Kendra is a natural language search service that uses machine learning for improved accuracy in search results and the ability to search unstructured data. In this course, you will learn about the benefits, features, typical use cases, technical concepts, and costs of Amazon Kendra. You will review an architecture for a search solution using Amazon Kendra that you can further adapt to your use case. Through a guided tutorial consisting of a narrated video, step-by-step instructions, and transcript, you will also try the service in your own Amazon Web Services (AWS) account. • Course level: Fundamental • Duration: 1.5 hours Activities: This course includes presentations and a step-by-step tutorial to follow along. Course objectives: In this course, you will do the following: • Understand how Amazon Kendra works. • Familiarize yourself with basic concepts of Amazon Kendra. • Recognize the benefits of Amazon Kendra. • List typical use cases for Amazon Kendra. • Describe the typical architectures associated with an Amazon Kendra solution. • Specify what it would take to implement Amazon Kendra in a real-world scenario. • Understand the cost structure of Amazon Kendra. • Implement a demonstration of Amazon Kendra in the AWS Management Console. Prerequisites We recommend that attendees of this course have completed the following trainings: • AWS Technical Essentials Course outline • Introduction to Amazon Kendra • Architecture and Use Cases • How Do You Create an Index in Amazon Kendra? • How Do You Add a Data Source in Amazon Kendra? • How Do You Create an FAQ with Amazon Kendra? • How Do You Delete Amazon Kendra Resources?
Amazon Transcribe Getting Started
Course description: Amazon Transcribe is a fully managed artificial intelligence (AI) service that helps you convert speech to text using automatic speech recognition (ASR) technology. In this Getting Started course, you will learn about the benefits, features, typical use cases, technical concepts, and costs of Amazon Transcribe. You will review an architecture for a transcription solution using Amazon Transcribe that you can further adapt to your use case. Through a guided tutorial consisting of narrated video, step-by-step instructions, and transcripts, you will also try real-time and batch transcription in your own Amazon Web Services (AWS) account. Course level: Fundamental • Duration: 1.5 hours Activities: This course includes presentations, graphics, and a step-by-step tutorial to follow along. Course objectives: In this course, you will do the following: • Understand how Amazon Transcribe works. • Familiarize yourself with basic concepts of Amazon Transcribe. • Recognize the benefits of Amazon Transcribe. • List typical use cases for Amazon Transcribe. • Describe the typical architectures associated with an Amazon Transcribe solution. • Specify what it would take to implement Amazon Transcribe in a real-world scenario. • Understand the cost structure of Amazon Transcribe. • Implement a demonstration of Amazon Transcribe in the AWS Management Console. Prerequisites We recommend that attendees of this course have completed the following trainings: • AWS Technical Essentials Course outline • Introduction to Amazon Transcribe • Architecture and Use Cases • How Do You Create a Real-Time Transcription in the AWS Management Console? • How Do You Create a Batch Transcription in the AWS Management Console? • How Do You Create a Transcription Using a Custom Vocabulary?
CloudEndure Migration Training – Technical
Description In this course, you will learn key CloudEndure Migration concepts, architecture, and implementation. A step-by-step walkthrough guides you through the entire CloudEndure Migration process. This training is recommended if you are actively working on migration projects using CloudEndure Migration or are assisting customers in doing so. This course focuses on the technical aspects of cloud migration, rather than the business aspects. Intended Audience This course is intended for: • Solutions architects and engineers who perform cloud migrations • IT project managers who are involved in projects related to migrating existing workloads to the AWS Cloud • Individuals who are part of an organization’s Cloud Center of Excellence (CCoE) Course Objectives In this course, you will learn how to: • List the benefits of migrating to the AWS Cloud using CloudEndure • Recognize CloudEndure terminology and basic concepts • Describe the keys to a successful implementation • Configure CloudEndure and AWS services to set up initial and nearly continuous data replication • Perform the steps necessary to migrate using CloudEndure • Troubleshoot common issues that can prevent successful implementation and replication. Prerequisites None Delivery Method This course is delivered through a mix of: • Digital training • Video Duration 2 hours Course Outline This course covers the following concepts: • CloudEndure Migration technology features and benefits • CloudEndure Migration lifecycle • CloudEndure Migration networking and architecture • Keys to a successful implementation • CloudEndure Migration steps • Managing large migrations
Introduction to Robotics on AWS
The robotics industry is growing at a rapid rate, creating a need for people with the varied skills required for robotics (mechanics, electrical, software, and more). In this course, you will learn how to use the cloud and Amazon Web Services (AWS) to help accelerate your robotics development. You will also learn about industry trends in robotics, the evolution to next-generation robotics in the cloud, and how AWS can solve common challenges for robotics companies. Finally, you will learn common patterns and best practices for robotics workloads on AWS. • Course level: Fundamental • Duration: 30 minutes Activities This course includes presentations, demonstrations, videos, and assessments. Course objectives In this course, you will learn to: • Understand the evolution of the robotics industry • Identify common robotics challenges • Identify the advantages of using AWS for robot development • Identify relevant AWS services for robotics workloads • Follow common patterns for robotics on AWS • Build modern applications for next-generation robots Intended audience This course is intended for: • Solutions architects • Software developers • Roboticists Prerequisites We recommend that attendees of this course have: • Understanding of basic robotics concepts such as sensors, actuators, and microcontrollers Course outline Module 1: Evolution of Robotics • Introduction • Industry trends in robotics • How the cloud is driving next-generation robots Module 2: Using AWS to Build Next-Generation Robots • Common challenges for building next-generation robots • Advantages to using AWS for robotic development • Taking your robots global Module 3: End-to-End Capabilities for Cloud Robotics on AWS • Common workflows and patterns for cloud robotics • Deploying software to fleets of devices • Streaming video and teleoperating your robot • Intelligent robots with machine learning inference • Testing and validating robots with simulation • Fleet monitoring and dashboarding • Fleet management • Gaining insights from robot data • Building a complete robot CI/CD pipeline
Getting Started with AWS Cloud Essentials
This course introduces you to cloud computing and the benefits of choosing AWS Cloud for your global infrastructure. Throughout this course, you will learn the key benefits of cloud computing and the core services offered by AWS Cloud. If you or your business are considering moving to the cloud, this course provides an overview of storage options, databases, networking setup, security, and pricing details. Getting Started with AWS Cloud Essentials also offers valuable resources, including user guides, references, and training certifications available based on roles or your desired solution. • Course level: Fundamental • Duration: 60 minutes Activities This course includes videos, reading text, and knowledge check questions. Course objectives In this course, you will learn to: • Differentiate between on-premise servers and cloud computing. • Identify the top benefits of cloud computing. • Recognize the AWS global infrastructure compared to on-premises. • Describe the core services offered by AWS Cloud, specifically regarding storage capabilities, database management, and networking. • Define the roles within the shared responsibility model. • Explore purchasing options available based on your business’s needs. Intended audience This course is intended for: • Solutions architects who are designing services or architectures that are integrated with databases • Software developers • AWS Solutions Architects • People who design cloud architectures Prerequisites We recommend that attendees of this course have: None Course outline Module 1: Navigation • How to Use This Course Module 2: Course Content • Getting Started in the AWS Cloud • Understanding the AWS Global Infrastructure • Core Services Overview: Compute • Core Services Overview: Storage • Core Services Overview: Databases • Core Services Overview: Networking • Core Services Overview: Security • Core Services Overview: Pricing • Next Steps Module 2: Thank You • Feedback
Getting Started with AWS Audit Manager
AWS Audit Manager helps you continuously audit your AWS usage and simplify risk and compliance assessment against regulations, internal control frameworks, and industry standards. Audit Manager automates evidence collection to reduce the manual effort of several cross-functional teams that audit activities often require. It can also help you to scale your auditing capabilities in the cloud as your business grows. In this course, you will learn the benefits, typical use cases, and technical concepts of Audit Manager. You will have an opportunity to try the service through demonstrations on the AWS Management Console. • Course level: Fundamental • Duration: 1.5 hours Activities This course includes presentations, graphics, and interactive activities. Course objectives In this course, you will learn to: • Understand how Audit Manager works. • Familiarize yourself with the technical concepts of Audit Manager. • List typical use cases for Audit Manager. • Specify what it would take to implement Audit Manager in a real-world scenario. • Recognize the benefits of Audit Manager. • Explain the cost structure of Audit Manager. • Show how to use Audit Manager from the AWS Management Console and using the AWS Command Line Interface (AWS CLI). Intended audience This course is intended for: • IT auditors • IT risk and compliance professionals • Security engineers supporting audit requests • Control/business owners of AWS Cloud workloads • DevOps administrators • Cloud administrators Prerequisites None Course outline • Introduction to Audit Manager • Architecture and Use Cases • How Do I Set Up Audit Manager? • How Do I Create an Assessment? • How Do I Review Assessment Findings with Audit Manager? • How Do I Use AWS CLI with Audit Manager? • How Do I Use AWS CloudFormation with Audit Manager? • How Do I Use Audit Manager with a Programming Language? • Learn More
Getting Started with Application Load Balancer
Amazon Application Load Balancer are deployed to provide scale, performance and resiliency for web application deployed on the cloud. Application Load Balancer distributes incoming application traffic at the layer 7 of OSI model, across multiple targets such as instances, containers and IP addresses, in one or more Availability Zones. In this “Getting Started” course, you will learn the benefits, typical use cases, and technical concepts of the Amazon Application Load Balancer. The course will allow you to try the service through provided Interactive Tool in the AWS Management Console. • Course level: Fundamental • Duration: 60 minutes Activities This course includes presentations, graphics, sample code, and interactive activities Course objectives In this course, you will learn to: • Understand how Amazon Application Load Balancer works. • Familiarize yourself with the technical concepts of Amazon Application Load Balancer. • List typical use cases for Amazon Application Load Balancer. • Specify what it would take to implement Amazon Load Balancer in a real-world scenario. • Recognize the benefits of Amazon Application Load Balancer. • Explain the cost structure of Amazon Application Load Balancer. • Show how to use Amazon Application Load Balancer from the AWS Management Console. Intended audience This course is intended for: • Developers • Solutions architects • Cloud practitioners • IT operations engineers • IT professionals • IT leaders Prerequisites No prerequisites needed. Course outline • Amazon Application Load Balancer Basics • Benefits of Amazon Application Load Balancer • Typical use cases for Amazon Application Load Balancer • Cost of running Amazon Application Load Balancer • How to manage Amazon Application Load Balancer via AWS Console • Learn More
Getting Started with Gateway Load Balancer
Amazon Gateway Load Balancer helps you deploy and manage thirdparty virtual appliances. Deploying third-party virtual appliances with your solution on Amazon Web Services (AWS) can be tricky. Gateway Load Balancer combines a transparent network gateway (a single entry and exit point for all traffic) and a load balancer that distributes traffic and scales virtual appliance with demand. In this “Getting Started” course, you will learn the benefits, typical use cases, and technical concepts of Gateway Load Balancer. • Course level: Fundamental • Duration: 60 minutes Activities This course includes presentations, graphics, knowledge checks, and interactive activities. Course objectives In this course, you will learn to: • Understand how Gateway Load Balancer works • Familiarize yourself with the technical concepts of Gateway Load Balancer • List typical use cases for Gateway Load Balancer • Specify what it would take to implement Amazon Location in a real-world scenario [A1] • Recognize the benefits of Gateway Load Balancer • Explain the cost structure of Gateway Load Balancer • Show how to use Amazon Location from the AWS Management Console [A2] Intended audience This course is intended for: • Developers • Solutions architects • Cloud practitioners • IT operations engineers • IT professionals • IT leaders Prerequisites No prerequisites needed. Course outline • Gateway Load Balancer Basics and Benefits • How to Architect a cCoud Solution Using Gateway Load Balancer • Typical Use Cases for Gateway Load Balancer • Gateway Load Balancer Pricing • How to Manage and Deploy Gateway Load Balancer • Learn More
Getting Started with Migration Hub Refactor Spaces
Are you ready to fast-track application refactoring? AWS Migration Hub Refactor Spaces is the new starting point for incremental app refactoring. Refactor Spaces can help reduce the business risk of evolving applications into microservices or extending existing applications with new features written in microservices. In this course, you will learn the benefits, use cases, and technical concepts of Refactor Spaces. You will have an opportunity to see the demonstration using the AWS Management Console. • Course level: Fundamental • Duration: 1 hour Activities This course includes presentations, architecture, and a demonstration with the option to follow along. Course objectives In this course, you will learn to: • Understand how Refactor Spaces works. • Familiarize yourself with the technical concepts to reduce the complexity of refactoring monoliths using the Strangler Fig pattern. • Explain architecture and use cases for Refactor Spaces. • Specify what it would take to refactor an application in a real-world scenario. • Recognize the benefits and explain the cost structure of Refactor Spaces. • Use Refactor Spaces from the AWS Management Console. Intended audience This course is intended for: • Developers • Solutions architects Prerequisites 1-plus years of development and architecture experience Course outline • Introduction to AWS Migration Hub Refactor Spaces • Using Refactor Spaces to Architect a Cloud Solution
Exam Readiness: AWS Certified Machine Learning – Specialty
This course prepares you to take the AWS Certified Machine Learning – Specialty exam, which validates your ability to design, implement, deploy, and maintain machine learning (ML) solutions. In this course, you’ll learn about the logistics of the exam and the mechanics of exam questions, and you’ll explore the exam’s technical domains. You’ll review core AWS services and key concepts for the exam domains: 1) Data Engineering 2)Exploratory Data Analysis 3)Modeling 4) Machine Learning Implementation and Operations You’ll also learn key test-taking strategies and will put them into action, taking multiple study questions. Once you’ve honed your skills, you’ll have the chance to take a quiz that will help you assess your areas of strength and weakness, so that you’ll know what to emphasize in your pre-exam studies. Course objectives: By the end of this course, you will be able to: •Identify your strengths and weaknesses in each exam domain so that you know what to focus on when studying for the exam •Describe the technical topics and concepts that make up each of the exam domains •Summarize the logistics and mechanics of the exam and its questions •Use effective strategies for studying and taking the exam Intended audience: This course is intended for: •ML practitioners who have at least one year of practical experience, and who are preparing to take the AWS Certified Machine Learning – Specialty exam Prerequisites: We recommend that attendees of this course have: •Proficiency expressing the intuition behind basic ML algorithms and performing basic hyperparameter optimization •Understanding of the ML pipeline and its components •Experience with ML and deep learning frameworks •Understanding of and experience in model training, deployment, and operational best practices [Enroll] (www.aws.training) Course outline: Module 0: Course Introduction: Module 1: Exam Overview and Test-taking Strategies: •Exam overview, logistics, scoring, and user interface •Question mechanics and design •Test-taking strategies Module 2: Domain 1 – Data Engineering: •Domain 1.1: Data Repositories for ML •Domain 1.2: Identify and implement a data-ingestion solution •Domain 1.3: Identify and implement a data-transformation solution •Walkthrough of study questions •Domain 1 quiz Module 3: Domain 2 – Exploratory Data Analysis: •Domain 2.1: Sanitize and prepare data for modeling •Domain 2.2: Perform featuring engineering •Domain 2.3: Analyze and visualize data for ML •Walkthrough of study questions •Domain 2 quiz Module 4: Domain 3 – Modeling: •Domain 3.1: Frame business problems as ML problems •Domain 3.2: Select the appropriate model(s) for a given ML problem •Domain 3.3: Train ML models •Domain 3.4 Perform hyperparameter optimization •Domain 3.5 Evaluate ML models •Walkthrough of study questions •Domain 3 quiz Module 5: Domain 4 – ML Implementation and Operations: •Domain 4.1: Build ML solutions for performance, availability, scalability, resiliency, and fault tolerance •Domain 4.2: Recommend and implement the appropriate ML services and features for a given problem •Domain 4.3: Apply basic AWS security practices to ML solutions •Domain 4.4: Deploy and operationalize ML solutions •Walkthrough of study questions •Domain 4 quiz Module 6: Additional Study Questions: •Opportunity to take additional study questions Module 7: Recommended Study Material: •Links to AWS blogs, documentation, FAQs, and other recommended study material for the exam Module 8: Course Wrap-up: •How to sign up for the exam •Course summary •Course feedback
