[2025 NEW] Data Engineering on AWS with Real World Hands On Project! Learn by doing!
*The hands on project will be using an AWS Free Tier resources.*
Building real world projects is proven to be the best way to retain knowledge and prove your expertise. These projects can be additional resource to be used during CV building and interview processes to explain experience with AWS Cloud and Data Engineering
AWS Certified Data Engineer Associate Exam (DEA-C01 or DE1-C01) is one of the tougher exams you can take. It covers a lengthy array of services and extensive preparation is required, watching videos in my experience usually doesnt cut it. Applying your learnings by doing will be a great way of ensuring that you really understand how these services work! This course gives you the best of both worlds by combining explanatory modules with hands on guidance.
In this course, I will guide you through the complete fundamentals needed to be a data engineer on AWS. I will explain fundamental data engineering concepts and demonstrate how to apply these concepts using AWS services. Throughout the course, you will gain hands-on experience by building an end-to-end data engineering solution, performing tasks like data ingestion, transformation, analysis, orchestration and visualisation. My goal is to prepare you to become a data engineer, understand data engineering practices as a solutions architect, pass the AWS DEA-C01 certification and help you succeed in your career.
Ive made sure to provide one of the most comprehensive and project based course out there today backed by instructors with extensive careers at AWS!
The course will cover the following :
Streaming and Batch ingestion of data with AWS DMS, Schema Conversion Tool, Apache Kafka, Amazon MSK, MSK Connect, Kinesis Data Streams, Kinesis Data Firehose, AWS Glue Schema Registry
Storage and Databases on Amazon S3, Amazon EBS, Amazon EFS, AWS Backup, Amazon RDS, Amazon Aurora, Amazon DynamoDB, Amazon Neptune, Amazon DocumentDB, Amazon Timestream, AWS Lake Formation
Transforming and processing with AWS Glue, Amazon EC2, Amazon ECR, Amazon ECS, Amazon EKS, Amazon EMR, AWS Batch, AWS Lambda, Managed Service for Apache Flink, Lambda
Analyse and query data on Amazon OpenSearch Service, Amazon Redshift, Amazon Athena
Schedule and Orchestrate the end-to-end pipeline and integrate with other services using Amazon EventBridge, AWS Step Functions, Apache Airflow MWAA, AWS Glue Workflows, Amazon SNS, Amazon SQS, Amazon AppFlow
Consume and Visualise data with Amazon QuickSight, Machine Learning, Amazon Sagemaker
Operationalise, maintain, and monitor data pipelines with Amazon CloudWatch and CloudTrail
Learn appropriate authentication, authorization, data encryption, privacy, and governance practices. Amazon IAM, Amazon KMS and AWS Secrets Manager
ETL pipeline concepts like Slowly Changing Dimensions (SCD I, SCD II)
CI/CD tools on AWS such as AWS CloudFormation, AWS Serverless Application Model AWS CodeCommit, AWS CodeBuild, AWS Code Deploy, AWS CodePipeline
Deep Dive on Open Source Technologies and SQL
Reading, writing and transforming data withApache Spark
Learn fundamentals of streaming with Apache Kafka
Understand architecture of OpenSearch
Write basic to intermediate queries and procedures with Structured Query Language (SQL)
Join me on this exciting journey and work towards achieving the Data Engineer Associate Exam (DEA-C01 or DE1-C01.
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