| Course Name |
Hours |
List Price |
Content |
| Advanced Developing on AWS |
21.00 |
$2,025.00 |
|
Description: The Advanced Developing on AWS course uses the real-world scenario of taking a legacy, on-premises monolithic application and refactoring it into a serverless microservices architecture. This three-day advanced course covers advanced development topics such as architecting for a cloud-native environment; deconstructing on-premises, legacy applications and repackaging them into cloud-based, cloud-native architectures; and applying the tenets of the Twelve-Factor Application methodology.
Skills Gained
In this course, you will learn how to:
Analyze a monolithic application architecture to determine logical or programmatic break points where the application can be broken up across different AWS services.
Apply Twelve-Factor Application manifesto concepts and steps while migrating from a monolithic architecture.
Recommend the appropriate AWS services to develop a microservices based cloud native application.
Use the AWS API, CLI, and SDKs to monitor and manage AWS services.
Migrate a monolithic application to a microservices application using the 6 Rs of migration.
Explain the SysOps and DevOps interdependencies necessary to deploy a microservices application in AWS. This course is intended for:
Experienced software developers who are already familiar with AWS services
# of Days:
Setting:
|
| Architecting on AWS |
21.00 |
$2,025.00 |
|
Description: Architecting on AWS covers the fundamentals of building IT infrastructure on AWS. The course is designed to teach solutions architects how to optimize the use of the AWS Cloud by understanding AWS services and how these services fit into cloud-based solutions. This course emphasizes AWS cloud best practices and recommended design patterns to help students think through the process of architecting optimal IT solutions on AWS. Case studies throughout the course showcase how some AWS customers have designed their infrastructures and the strategies and services they implemented.
# of Days:
Setting:
|
| Architecting on AWS Accelerator |
35.00 |
$3,150.00 |
|
Description: This course combines Architecting on AWS and Advanced Architecting on AWS to offer a comprehensive, immersive course in cloud architecture. It covers all aspects of how to architect for the cloud over 5 days. You will learn how to design cloud architectures, starting small and working to large-scale enterprise level designsand everything in between. Starting with the Well Architected Framework, you will be immersed in AWS services like compute, storage, database, networking, security, monitoring, automation, optimization, benefits of de-coupling applications and serverless, building for resilience, and understanding costs. Using hands-on labs, you will apply knowledge from lectures to gain skills.
Skills Gained
Make architectural decisions based on AWS architectural principles and best practices
Use AWS services to make your infrastructure scalable, reliable, and highly available
Use AWS Managed Services to enable greater flexibility and resiliency in an infrastructure
Make an AWS-based infrastructure more efficient to increase performance and reduce costs
Use the Well Architected Framework to improve architectures with AWS solutions Who Can Benefit
Who Can Benefit
This course is intended for:
Solutions Architects who are new to designing and building cloud architectures
Data Center Architects who are migrating from on-premises environment to cloud architectures
Other IT/cloud roles who want to understand how to design and build cloud architectures
# of Days:
Setting:
|
| AWS Certification Exam Readiness Workshop: AWS Certified Solutions Architect Associate |
4.00 |
$300.00 |
|
Description: The AWS Certified Solutions Architect Associate exam validates technical expertise in designing and deploying scalable, highly available, and fault-tolerant systems on the AWS platform. In this half-day, intermediate-level workshop, we will explore the exams topic areas, mapping them to architecting on AWS and to specific areas to study. We will review sample exam questions in each topic area, teaching you how to interpret the concepts being tested so that you can better eliminate incorrect responses.
Skills Gained
This workshop is designed to teach you how to:
What to expect from the exam
How the exam is structured, including question types
How to determine how questions relate to AWS architectural concepts
How to interpret the concepts being tested by an exam question
How to allocate your study time for the exam
Who Can Benefit
This workshop is intended for:
Individuals who are preparing to take the AWS Certified Solutions Architect Associate exam
Solutions architects
# of Days:
Setting:
|
| AWS Cloud Practitioner Essentials |
7.00 |
$675.00 |
|
Description: The fundamental-level full day course is intended for individuals who seek an overall understanding of the AWS Cloud, independent of specific technical roles. It provides a detailed overview of cloud concepts, AWS services, security, architecture, pricing, and support. It includes lab exercises reinforcing some of the core concepts of the lecture. This course also helps you prepare for the AWS Certified Cloud Practitioner exam. This course includes AWS Training Exclusives.
Skills Gained
Define what the cloud is and how it works
Differentiate between cloud computing and deployment models
Describe the AWS Cloud value proposition
Describe the basic global infrastructure of the cloud
Compare the different methods of interacting with AWS
Describe and differentiate between AWS service domains
Given a scenario, identify an appropriate solution using AWS Cloud services
Describe the Well-Architected Framework
Describe basic AWS Cloud architectural principles
Explain the Shared Responsibility model
Describe security services with the AWS cloud
Define the billing, account management, and pricing models for the AWS platform
Identify future services and developments built on the cloud
Who Can Benefit
Sales
Legal
Marketing
Business analysts
Project managers
AWS Academy students
Other IT-related professionals
# of Days:
Setting:
|
| AWS Security Essentials |
7.00 |
$640.00 |
|
Description: This course covers fundamental AWS cloud security concepts, including AWS access control, data encryption methods, and how network access to your AWS infrastructure can be secured. Based on the AWS Shared Security Model, you learn where you are responsible for implementing security in the AWS Cloud and what security-oriented services are available to you and why and how the security services can help meet the security needs of your organization.
Skills Gained
In this course, you will learn how to:
Assimilate Identify security benefits and responsibilities of using the AWS Cloud
Describe the access control and management features of AWS
Explain the available methods for providing encryption of data in transit and data at rest when storing your data in AWS.
Describe how to secure network access to your AWS resources
Determine which AWS services can be used for monitoring and incident response
Who Can Benefit
This course is intended for:
Security IT business-level professionals interested in cloud security practices
Security professionals with minimal to no working knowledge of AWS
# of Days:
Setting:
|
| AWS Technical Essentials (AWS-T-ESS) |
7.00 |
$699.00 |
|
Description: AWS Technical Essentials introduces you to AWS products, services, and common solutions. It provides IT technical end users with basic fundamentals to become more proficient in identifying AWS services so that you can make informed decisions about IT solutions based on your business requirements.
# of Days:
Setting:
|
| AWS: Advanced Architecting on AWS |
21.00 |
$2,025.00 |
|
Description: Advanced Architecting on AWS is intended for individuals who are experienced with designing scalable and elastic applications on the AWS platform. Building on concepts introduced in Architecting on AWS, this course covers how to build complex solutions that incorporate data services, governance, and security on AWS. This course introduces specialized AWS services, including AWS Direct Connect and AWS Storage Gateway to support hybrid architecture. It also covers designing best practices for building scalable, elastic, secure, and highly available applications on AWS.
# of Days:
Setting:
|
| AWS: Developing on AWS |
21.00 |
$2,025.00 |
|
Description: Developing on AWS helps developers understand how to use the AWS SDK to develop secure and scalable cloud applications. The course provides in-depth knowledge about how to interact with AWS using code and covers key concepts, best practices, and troubleshooting tips.
Skills Gained
This course is designed to teach you how to:
Set up the AWS SDK and developer credentials for Java, C/.NET, and Python
Interact with AWS services and develop solutions by using the AWS SDK
Use AWS Identity and Access Management (IAM) for service authentication
Use Amazon Simple Storage Service (Amazon S3) and Amazon DynamoDB as data stores
Integrate applications and data by using AWS Lambda, Amazon API Gateway, Amazon Simple Queue Service (Amazon SQS), Amazon Simple Notification Service (Amazon SNS), and AWS Step Functions
Use Web Identity Framework and Amazon Cognito for user authentication
Use Amazon ElastiCache to improve application scalability
Use containers in the development process
Leverage the CI/CD pipeline to deploy applications on AWS
# of Days:
Setting:
|
| AWS: DevOps Engineering on AWS |
21.00 |
$2,025.00 |
|
Description: DevOps Engineering on AWS demonstrates how to use the most common DevOps patterns to develop, deploy, and maintain applications on AWS. The course covers the core principles of the DevOps methodology and examines a number of use cases applicable to startup, small and medium-sized business, and enterprise development scenarios.
Skills Gained
This course is designed to teach you how to:
Use the principal concepts and practices behind the DevOps methodology
Design and implement an infrastructure on AWS that supports one or more DevOps development projects
Use AWS CloudFormation and AWS OpsWorks to deploy the infrastructure necessary to create development, test, and production environments for a software development project
Use AWS CodeCommit and understand the array of options for enabling a Continuous Integration environment on AWS
Use AWS CodePipeline to design and implement a Continuous Integration and Delivery pipeline on AWS
Implement several common Continuous Deployment use cases using AWS technologies, including blue/green deployment and A/B testing
Distinguish between the array of application deployment technologies available on AWS (including AWS CodeDeploy, AWS Opsworks, AWS Elastic Beanstalk, Amazon EC2 Container Service, and Amazon EC2 Container Registry), and decide which technology best fits a given scenario
Fine tune the applications you deliver on AWS for high performance and use AWS tools and technologies to monitor your application and environment for potential issues
# of Days:
Setting:
|
| Data Warehousing on AWS |
21.00 |
$2,025.00 |
|
Description: Data Warehousing on AWS introduces you to concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift, the petabyte-scale data warehouse in AWS. This course demonstrates how to collect, store, and prepare data for the data warehouse by using other AWS services such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis Firehose, and Amazon S3. Additionally, this course demonstrates how to use business intelligence tools to perform analysis on your data.
Skills Gained
This course teaches you how to:
Discuss the core concepts of data warehousing.
Evaluate the relationship between Amazon Redshift and other big data systems.
Evaluate use cases for data warehousing workloads and review case studies that demonstrate implementation of AWS data and analytic services as part of a data warehousing solution.
Choose an appropriate Amazon Redshift node type and size for your data needs.
Discuss security features as they pertain to Amazon Redshift, such as encryption, IAM permissions, and database permissions.
Launch an Amazon Redshift cluster and use the components, features, and functionality to implement a data warehouse in the cloud.
Use other AWS data and analytic services, such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis Firehose, and Amazon S3, to contribute to the data warehousing solution.
Evaluate approaches and methodologies for designing data warehouses.
Identify data sources and assess requirements that affect the data warehouse design.
Design the data warehouse to make effective use of compression, data distribution, and sort methods.
Load and unload data and perform data maintenance tasks.
Write queries and evaluate query plans to optimize query performance.
Configure the database to allocate resources such as memory to query queues and define criteria to route certain types of queries to your configured query queues for improved processing.
Use features and services, such as Amazon Redshift database audit logging, Amazon CloudTrail, Amazon CloudWatch, and Amazon Simple Notification Service (Amazon SNS), to audit, monitor, and receive event notifications about activities in the data warehouse.
Prepare for operational tasks, such as resizing Amazon Redshift clusters and using snapshots to back up and restore clusters.
Use a business intelligence (BI) application to perform data analysis and visualization tasks against your data.
Who Can Benefit
Database architects
Database administrators
Database developers
Data analysts and scientists
# of Days:
Setting:
|
| Deep Learning on AWS |
7.00 |
$675.00 |
|
Description: Deep Learning on AWS is a one-day course that introduces you to cloud-based Deep Learning (DL) solutions on Amazon Web Services (AWS). The training will detail how deep learning is useful and explain its different concepts. This course also teaches you how to run your models on the cloud using Amazon SageMaker, Amazon Elastic Compute Cloud (Amazon EC2)-based Deep Learning Amazon Machine Image (AMI) and MXNet framework. In addition, you will gain a better understanding of deploying your deep learning models using AWS services like AWS Lambda and Amazon EC2 Container Service (Amazon ECS) while designing intelligent systems on AWS, based on Deep Learning.
# of Days:
Setting:
|
| Migrating to AWS |
14.00 |
$1,350.00 |
|
Description: Migrating to AWS focuses on planning and migrating existing workloads to the AWS Cloud. The course covers various cloud migration strategies with a detailed discussion on each phase of the migration process, including portfolio discovery, application migration planning and design, migration execution, and post-migration validation and application optimization. The first part of the course provides students with an overview of migration planning principles and best practices, and the second half of the class focuses on migration design and implementation with hands-on labs to reinforce concepts.
This course is designed for solutions architects and engineers who perform cloud migrations and have an understanding of core AWS services and design patterns covered in Architecting on AWS, and is also available to IT project managers involved in the planning of those migrations who have completed AWS Technical Essentials.
Skills Gained
This course teaches you how to:
Explain the various cloud migration strategies.
Assess cloud migration readiness.
Discover your portfolio and plan for migration.
Plan and design your application migration strategy.
Perform and validate application migration to the cloud.
Optimize your applications and operations after migrating to the cloud.
Who Can Benefit
This course is intended for:
Solutions Architects and engineers who perform cloud migrations and have completed AWS Technical Essentials or Architecting on AWS
IT Project Managers who are involved in projects related to migrating existing workloads to the AWS Cloud and have completed AWS Technical Essentials or Architecting on AWS
Individuals who are part of an organizations cloud Center of Excellence (CoE)
# of Days:
Setting:
|
| Planning and Designing Databases on AWS |
21.00 |
$2,025.00 |
|
Description: In this course, you will learn about the process of planning and designing both relational and nonrelational databases. You will learn the design considerations for hosting databases on Amazon Elastic Compute Cloud (Amazon EC2). You will learn about our relational database services including Amazon Relational Database Service (Amazon RDS), Amazon Aurora, and Amazon Redshift. You will also learn about our nonrelational database services including Amazon DocumentDB, Amazon DynamoDB, Amazon ElastiCache, Amazon Neptune, and Amazon QLDB. By the end of this course, you will be familiar with the planning and design requirements of all 8 of these AWS databases services, their pros and cons, and how to know which AWS databases service is right for your workloads.
Skills Gained
Apply database concepts, database management, and data modeling techniques
Evaluate hosting databases on Amazon EC2 instances
Evaluate relational database services (Amazon RDS, Amazon Aurora, and Amazon Redshift) and their features
Evaluate nonrelational database services (Amazon DocumentDB, Amazon DynamoDB, Amazon ElastiCache, Amazon Neptune, and Amazon QLDB) and their features
Examine how the design criteria apply to each service
Apply management principles based on the unique features of each service
Who Can Benefit
Data platform engineers, Database administrators, Solutions architects, IT professionals
# of Days:
Setting:
|
| Practical Data Science with Amazon SageMaker |
7.00 |
$675.00 |
|
Description: In this intermediate-level course, individuals learn how to solve a real-world use case with Machine Learning (ML) and produce actionable results using Amazon SageMaker. This course walks through the stages of a typical data science process for Machine Learning from analyzing and visualizing a dataset to preparing the data, and feature engineering. Individuals will also learn practical aspects of model building, training, tuning, and deployment with Amazon SageMaker. Real life use cases include customer retention analysis to inform customer loyalty programs.
# of Days:
Setting:
|
| Security Engineering on AWS |
21.00 |
$2,025.00 |
|
Description: This course demonstrates how to efficiently use AWS security services to stay secure in the AWS Cloud. The course focuses on the security practices that AWS recommends for enhancing the security of your data and systems in the cloud. The course highlights the security features of AWS key services including compute, storage, networking, and database services. You will also learn how to leverage AWS services and tools for automation, continuous monitoring and logging, and responding to security incidents.
Skills Gained
This course teaches you how to:
Assimilate and leverage the AWS shared security responsibility model
Architect and build AWS application infrastructures that are protected against the most common security threats
Protect data at rest and in transit with encryption
Apply security checks and analyses in an automated and reproducible manner
Configure authentication for resources and applications in the AWS Cloud
Gain insight into events by capturing, monitoring, processing, and analyzing logs
Identify and mitigate incoming threats against applications and data
Perform security assessments to ensure that common vulnerabilities are patched and security best practices are applied
Who Can Benefit
This course is intended for:
Security engineers
Security architects
Security operations
Information security
# of Days:
Setting:
|
| Systems Operations on AWS |
21.00 |
$2,025.00 |
|
Description: System Operations on AWS is designed to teach those in a Systems Administrator or Developer Operations (DevOps) role how to create automatable and repeatable deployments of networks and systems on the AWS platform. The course covers the specific AWS features and tools related to configuration and deployment, as well as common techniques used throughout the industry for configuring and deploying systems.
# of Days:
Setting:
|
| The Machine Learning Pipeline on AWS |
28.00 |
$2,700.00 |
|
Description: Learn how to use the machine learning (ML) pipeline with Amazon SageMaker with hands-on exercises and four days of instruction. You will learn how to frame your business problems as ML problems and use Amazon SageMaker to train, evaluate, tune, and deploy ML models. Hands-on learning is a key component of this course, so youll choose a project to work on, and then apply the knowledge and skills you learn to your chosen project in each phase of the pipeline. Youll have a choice of projects: fraud detection, recommendation engines, or flight delays.
# of Days:
Setting:
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