Amazon Web Services (AWS)
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BD-AWS
Big Data on AWS
3 Днів, 24 Ак. Годин
BD-AWS
Building Data Lakes on AWS
1 Днів, 8 Ак. Годин
DW-AWS
Data Warehousing on AWS
3 Днів, 24 Ак. Годин
DL-AWS
Deep Learning on AWS
1 Днів, 8 Ак. Годин
D-AWS
Developing on AWS
3 Днів, 24 Ак. Годин
DOE-AWS
DevOps Engineering on AWS
3 Днів, 24 Ак. Годин
M-AWS
Migrating to AWS
2 Днів, 16 Ак. Годин
PDD-AWS
Planning and Designing Databases on AWS
3 Днів, 24 Ак. Годин
PDSASM
Practical Data Science with Amazon SageMaker
1 Днів, 8 Ак. Годин
RCEM-AWS
Running Container-Enabled Microservices on AWS
1 Днів, 8 Ак. Годин
BD-AWS
Big Data on AWS
In this course, you’ll learn about cloud-based big data solutions like Amazon EMR, Amazon Redshift, Amazon Kinesis, and the rest of the AWS big data platform. Learn to use Amazon EMR to process data using the broad ecosystem of Hadoop tools like Hive and Hue, create big data environments, work with Amazon DynamoDB, Amazon Redshift, Amazon QuickSight, Amazon Athena and Amazon Kinesis, and design big data environments for security and cost-effectiveness.
Аудиторно, дистанційно
3 Днів, 24 Ак. Годин
BD-AWS
Building Data Lakes on AWS
In this course, you will learn how to build an operational data lake that supports analysis of both structured and unstructured data. You will learn the components and functionality of the services involved in creating a data lake. You will use AWS Lake Formation to build a data lake, AWS Glue to build a data catalog, and Amazon Athena to analyze data. The course lectures and labs further your learning with the exploration of several common data lake architectures.
Аудиторно, дистанційно
1 Днів, 8 Ак. Годин
DW-AWS
Data Warehousing on AWS
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 AWS services such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3. Additionally, this course demonstrates how to use Amazon QuickSight to perform analysis on your data.
Аудиторно, дистанційно
3 Днів, 24 Ак. Годин
DL-AWS
Deep Learning on AWS
In this course, you’ll learn about AWS’s deep learning solutions, including scenarios where deep learning makes sense and how deep learning works. You’ll learn how to run deep learning models on the cloud using Amazon SageMaker and the MXNet framework. You’ll also learn to deploy your deep learning models using services like AWS Lambda while designing intelligent systems on AWS.
Аудиторно, дистанційно
1 Днів, 8 Ак. Годин
D-AWS
Developing on AWS
Learn how to use the AWS Software Development Kit to develop secure and scalable cloud applications. You will be able to setup AWS SDK and developer
credentials for Java, C#/.NET, Python, and JavaScript. Explore how to interact with AWS services, and develop solutions by using the AWS SDK. Also learn about key concepts, best practices, and troubleshooting tips.
credentials for Java, C#/.NET, Python, and JavaScript. Explore how to interact with AWS services, and develop solutions by using the AWS SDK. Also learn about key concepts, best practices, and troubleshooting tips.
Аудиторно, дистанційно
3 Днів, 24 Ак. Годин
DOE-AWS
DevOps Engineering on AWS
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.
Аудиторно, дистанційно
3 Днів, 24 Ак. Годин
M-AWS
Migrating to AWS
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. This course is designed for Solutions Architects and Engineers who perform cloud migrations, have an understanding of core AWS services and design patterns covered in Architecting on AWS. This course is also available to IT project managers involved in the planning of those migrations who have completed AWS Technical Essentials.
Аудиторно, дистанційно
2 Днів, 16 Ак. Годин
PDD-AWS
Planning and Designing Databases on AWS
In this course, you will learn about the process of planning and designing both relational and nonrelational AWS databases. It will teach you how to use workload requirements to define database design considerations and also explore the features and capabilities of the eight AWS database services. By the end of the course, you will be able to determine which AWS database service is right for your workloads, and design the database to meet your requirements.
Аудиторно, дистанційно
3 Днів, 24 Ак. Годин
PDSASM
Practical Data Science with Amazon SageMaker
In this intermediate-level course, you will 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 case includes customer retention analysis to inform customer loyalty programs.
Аудиторно, дистанційно
1 Днів, 8 Ак. Годин
RCEM-AWS
Running Container-Enabled Microservices on AWS
Running Container-Enabled Microservices on AWS is designed to teach you how to manage and scale container-enabled applications by using Amazon Elastic Container Service (ECS). This course highlights the challenges of running containerized applications at scale and provides guidance on creating and using Amazon ECS to develop and deploy containerized microservices-based applications. In the hands-on lab exercises you will use Amazon ECS to handle long-running services, build and deploy container images, link services together, and scale capacity to meet demand. You will also learn how to run container workers for asynchronous application processes.
Аудиторно, дистанційно
1 Днів, 8 Ак. Годин
BD-AWS
Big Data on AWS
Формат
Днів
3 Днів, 24 Ак. Годин
BD-AWS
Building Data Lakes on AWS
Формат
Днів
1 Днів, 8 Ак. Годин
DW-AWS
Data Warehousing on AWS
Формат
Днів
3 Днів, 24 Ак. Годин
DL-AWS
Deep Learning on AWS
Формат
Днів
1 Днів, 8 Ак. Годин
D-AWS
Developing on AWS
Формат
Днів
3 Днів, 24 Ак. Годин
DOE-AWS
DevOps Engineering on AWS
Формат
Днів
3 Днів, 24 Ак. Годин
M-AWS
Migrating to AWS
Формат
Днів
2 Днів, 16 Ак. Годин
PDD-AWS
Planning and Designing Databases on AWS
Формат
Днів
3 Днів, 24 Ак. Годин
PDSASM
Practical Data Science with Amazon SageMaker
Формат
Днів
1 Днів, 8 Ак. Годин
RCEM-AWS
Running Container-Enabled Microservices on AWS
Формат
Днів
1 Днів, 8 Ак. Годин
