Best Free Kinesis Courses

Best Free Kinesis Courses

Do you want to learn Kinesis? Here we listed Best Free Amazon Kinesis Courses which will help you learn Amazon Kinesis, and are suitable for beginners, intermediate learners as well as experts.

Introduction to Amazon Kinesis Analytics


This is an introductory course on Amazon Kinesis Analytics, which helps you query streaming data or build entire streaming applications using SQL. In this course, we discuss how the service collects, processes and analyzes streaming data in real-time. We also discuss how to use and monitor Amazon Kinesis Analytics and explore use cases.

Trainer: AWS

Introduction to Amazon Kinesis Data Analytics for Java Applications


The new support for Java programming in Amazon Kinesis Data Analytics helps you solve challenges, and this course will show you how. You’ll also learn how the SDKs are supported through Apache Flink libraries and see how it works in real-world use cases.

Trainer: AWS

Introduction to Amazon Kinesis Firehose


Amazon Kinesis Firehose is the AWS service that helps you load streaming data into AWS. In this introductory course on Amazon Kinesis Firehose, we will provide an overview on how the service captures, transforms and loads streaming data into AWS by detailing the data transformation process. We will look at the benefits of the service and how it integrates with Amazon CloudWatch to enable stream monitoring. The course will wrap up with a demonstration on how to configure a Kinesis Firehose delivery stream and how to generate source stream content.

Trainer: AWS
Introduction to Amazon Kinesis Streams


In this course, we cover how Amazon Kinesis Streams is used to collect, process and analyze real-time streaming data to create valuable insights. An overview of the components of this service and a brief demonstration are also covered in this course.

Trainer: AWS
Anomaly Detection on AWS


Explore some of the more practical aspects of building anomaly detection applications on AWS, using Amazon Kinesis Data Analytics and Amazon SageMaker.

Trainer: AWS
Data Analytics Fundamentals

Learn how to:

  • Identify the characteristics of data analysis solutions and the characteristics that indicate such a solution may be required
  • Define types of data including structured, semistructured, and unstructured data
  • Define data storage types such as data lakes, AWS Lake Formation, data warehouses, and the Amazon Simple Storage Service (Amazon S3)
  • Analyze the characteristics of and differences in batch and stream processing
  • Define how Amazon Kinesis is used to process streaming data
  • Analyze the characteristics of different storage systems for source data
  • Analyze the characteristics of online transaction processing (OLTP) and online analytical processing (OLAP) systems and their impact on the organization of data within these systems
  • Analyze the differences of row-based and columnar data storage methods
  • Define how Amazon EMR, AWS Glue, and Amazon Redshift each work to process, cleanse, and transform data within a data analysis solution
  • Analyze the concept of atomicity, consistency, isolation, and durability (ACID) compliance as well as basic availability, soft state, eventual consistency (BASE) compliance and how an extract, transform, load (ETL) process can help to ensure compliance
  • Explore the concept of data schemas and understand how they define data and how this information is stored in metastores
  • Analyze the concept of data versus information
  • Recognize the ways to analyze data to produce information for reports using tools such as Amazon QuickSight and Amazon Athena
  • Define how AWS services work together to visualize data
Trainer: AWS
Introduction to Amazon Kinesis

What you’ll learn

  • Introduction to Collecting Data: In this lesson, we’ll prepare you for what we’ll be covering in the course; the Big Data collection services of AWS Data Pipeline, Amazon Kinesis, and AWS Snowball.
  • Introduction to Data Pipeline: In this lesson, we’ll discuss the basics of Data Pipeline.
  • AWS Data Pipeline Architecture: In this lesson, we’ll go into more detail about the architecture that underpins the AWS Data Pipeline Big Data Service.
  • AWS Data Pipeline Core Concepts: In this lesson, we’ll discuss how we define data nodes, access, activities, schedules, and resources.
  • AWS Data Pipeline Reference Architecture: In this lesson, we’ll look at a real-life scenario of how data pipeline can be used.
  • Introduction to AWS Kinesis: In this lesson, we’ll take a top-level view of Kinesis and its uses.
  • Kinesis Streams Architecture: In this lesson, we’ll look at the architecture that underpins Kinesis.
  • Kinesis Streams Core Concepts: In this lesson, we’ll dig deeper into the data records.
  • Kinesis Streams Firehose Architecture: In this lesson, we’ll look at firehose architecture and the differences between it and Amazon Kinesis Streams.
  • Firehose Core Concepts: Let’s take a deeper look at some details about the Firehose service.
  • Kinesis Wrap-Up: In this summary, we’ll look at the differences between Kinesis and Firehose.
  • Introduction to Snowball: Overview of the Snowball Service.
  • Snowball Architecture: Let’s have a look at the architecture that underpins the AWS Snowball big data service
  • Snowball Core Concepts: In this lesson, we’ll look at the details of how Snowball is engineered to support data transfer.
  • Snowball Wrap-Up: A brief summary of Snowball and our course.
Trainer: Shane Gibson

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