The "Become a Data Engineer" courses cover the following key topics:
Data Engineering Fundamentals - enterprise data landscape, what data engineering actually is, the importance of data engineering, skills required and key responsibilities of a data engineer
Key Components of an Enterprise Data Platform - overall data architecture, data warehousing, data lake, lakehouse, data computing framework
Data Pipelines : Extract, Transform and Load - what a data pipeline is , the importance of data pipelines, the key components of data pipelines, common and reusable design patterns of data pipelines, what it takes to productionize data pipelines
Build an Enterprise Data Platform on AWS - key data services on AWS including S3, EMR, Glue, Athena and so on. Reusable implementation patterns for data ingestion, transformation and loading on AWS. You will have the skills, knowledge and confidence to pass the certificate exam of AWS Certified Big Data - Specialty Certification
Build an Enterprise Data Platform on Azure - key data services on Azure including ADLS, Synapse, HDInsight, Azure Data Factory and so on. Reusable implementation patterns for data ingestion, transformation and loading on Azure. You will have the skills, knowledge and confidence to pass the certificate exam of Azure Data Engineer
Build an Enterprise Data Platform on GCP - key data services on GCP including GCS, BigQuery, Dataflow, Dataproc and so on. Reusable implementation patterns for data ingestion, transformation and loading on GCP. You will have the skills, knowledge and confidence to pass the certificate exam of GCP Professional Data Engineer
