HRDC Reg. No: 10001547674
Duration: 4 Days (28 Hours)
Course Overview
This hands-on course provides a comprehensive guide to designing and implementing Big Data and Machine Learning solutions on AWS. It covers key AWS services such as EMR, Redshift, Glue, Kinesis, Athena, DynamoDB, and Airflow. Participants will learn to build scalable, secure, and cost-effective data pipelines and architectures using cloud-native services for ingestion, transformation, analysis, and orchestration.
Who Should Attend
Targeted Industries
Why Choose This Course
HRDC Claimable – [TBD]
Designed for teams moving their data workloads to AWS, this course equips participants with both foundational knowledge and advanced practical skills to harness the full potential of AWS Big Data services.
Learning Outcomes
By the end of this course, participants will be able to:
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Understand AWS cloud architecture and Big Data ecosystem
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Ingest and analyze structured/unstructured data using AWS tools
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Build data pipelines with Kinesis, Glue, Athena, and EMR
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Optimize storage with S3 and databases with Redshift, RDS, and DynamoDB
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Automate workflows using Airflow and Lambda
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Secure and monitor AWS Big Data environments
Prerequisites
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Familiarity with Hadoop, Spark, Hive, and HDFS
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Programming in Python
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Knowledge of SQL/NoSQL and database design
Lab Setup
Access & Infrastructure:
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Free-tier AWS account recommended
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Connectivity to AWS over HTTP, SSH, and TCP
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Public IP whitelisting and AWS Infra Readiness guidance provided
Lab Activities:
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Guided exercises with S3, Athena, Glue, EMR, Redshift, and Airflow
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Real-world data sets and project simulations
Teaching Methodology