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Learners Enrolled : 10
Created by Soumyadeep Dey
English
This is Volume 1 of Data Engineering course on AWS. In this course I will talk about the Data Warehouse and OLAP (Online Analytical Processing) technologies on AWS. It will give you detailed explanations on AWS Data Engineering Services like S3 (Simple Storage Service), Redshift, Athena, Hive, Glue Data Catalog, Lake Formation. This course delves into the data warehouse or consumption and storage layer of Data Engineering pipeline. At the end of the course, you will get to do 10 different projects that match real life scenarios with approx. 200 GB of data.
In Volume 2, I will showcase Data Processing (Batch and Streaming) Services.
You will get opportunities to do hands-on using large datasets (100 GB - 200 GB or more of data). Moreover, this course will provide you hands-on exercises that match with real-time scenarios like Redshift query performance tuning, streaming ingestion, Window functions, ACID transactions, COPY command, Distributed & Sort key, WLM, Row level and column level security, Athena partitioning, Athena WLM etc.
Some other highlights:
Live sessions (6-8 hrs) every week. Link of the sessions will be shared once you enrol. Recording for the live sessions will be made available to all learners.
Our curriculum is designed to take you from Beginner level to Expert level using production size datasets and production like scenarios for all courses.
Interact and network with like-minded folks from various backgrounds in Live Sessions.
Stuck on something? Discuss it with your peers and the instructors in the inbuilt chat groups.
Each course contains minimum of 8 to 10 projects with min of 150 - 200 GB of datasets. It is highly recommended to complete all the projects to get understanding of real life scenarios.
Flaunt your skills with course certificates. You can showcase the certificates on LinkedIn with a click.
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