Course Title:

AWS Data and Analytics: Big Data Solutions

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Overview:

This course provides a comprehensive exploration of AWS data and analytics services, focusing on leveraging these tools for big data processing, storage, and analysis. Participants will gain hands-on experience with key AWS services like Amazon Redshift, Amazon EMR, Amazon S3, and more. The course also covers machine learning and AI applications using AWS, helping participants understand how to implement and optimize big data solutions in the cloud.

Duration:

3 days

Target Participants:

This course is designed for data engineers, data scientists, IT professionals, and developers who are interested in learning how to use AWS for big data solutions. It is also suitable for business analysts and decision-makers looking to leverage data analytics and machine learning in their organizations.

Course Outcomes:

By the end of this course, participants will:

  • Understand the range of AWS data services available and their use cases.
  • Be able to implement data storage and migration strategies using Amazon S3.
  • Gain skills in processing and analyzing big data using Amazon EMR, Redshift, and Kinesis.
  • Learn to set up and manage search and analytics using Amazon Elasticsearch.
  • Be introduced to AWS machine learning services and how to build models using Amazon SageMaker.
  • Be capable of creating data visualizations and reports using Amazon QuickSight.
  • Apply best practices in data and analytics within AWS.

Course Content:

  • Overview of AWS data services
  • Introduction to Amazon Redshift, Athena, and Glue
  • Working with Amazon S3 for data storage
  • Data migration strategies
  •  
  • Processing data with Amazon EMR
  • Data warehousing with Amazon Redshift
  • Real-time analytics with Amazon Kinesis
  • Using Amazon Elasticsearch for search and analytics
  • Introduction to AWS machine learning services
  • Building ML models with Amazon SageMaker
  • Analyzing data with Amazon QuickSight
  • Use cases and best practices for AWS data and analytics services

Register Courses:

Training Methodology:

The course will utilize a blend of lectures, hands-on labs, group discussions, and case studies. Participants will engage in practical exercises to apply the concepts learned, ensuring a deep understanding of AWS services and their real-world applications.

Training Tools:

  • AWS Management Console
  • AWS SDKs and CLI
  • Amazon S3, Redshift, EMR, Kinesis, Elasticsearch, SageMaker, and QuickSight
  • Sample datasets for hands-on labs
  • Online collaboration tools for group activities

Training Preparation:

Participants are advised to:

  • Have an AWS account set up before the course.
  • Familiarize themselves with basic cloud computing concepts.
  • Review introductory materials on AWS data services (provided upon registration).

Training Prerequisites

  • Basic understanding of data processing concepts and database systems.
  • Familiarity with programming or scripting languages (Python, SQL) is recommended but not required.
  • Prior experience with AWS or other cloud platforms is beneficial but not mandatory.

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