Module 1: SQL (PostgreSQL/Oracle)
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Introduction to SQL & Database Concepts
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Normalization & Entity Relationship Model
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SQL Operators & Query Optimization
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Joins, Tables, and Variables in SQL
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Deep Dive into SQL Functions & Subqueries
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SQL Views, Stored Procedures, & User-Defined Functions
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Managing Database Concurrency & SQL Parsing
Module 2: Python for Data Engineering
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Python Basics & OOPs Concepts
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NumPy & Pandas for Data Processing
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Data Visualization Techniques
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File & Exception Handling
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Regular Expressions for Data Manipulation
Module 3: Linux for Data Engineers
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Linux Basics & File System Navigation
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File/Text Manipulation & Process Management
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User & Group Management
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Networking, System Monitoring, & Logging
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Shell Scripting & Security Best Practices
Module 4: Data Modeling
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Core Concepts of Data Modeling
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Entity, Class, and Attribute Relationships
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Conceptual, Logical & Physical Data Modeling
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Data Modeling Tools & Documentation
Module 5: AWS Big Data
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AWS Basics & Cloud Data Engineering
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Amazon Kinesis & Managed Streaming for Apache Kafka
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AWS Glue for Data Transformation
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Amazon EMR, S3, Glacier & DynamoDB
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AWS Redshift, Athena & QuickSight
Module 6: Azure Data Engineering
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Introduction to Microsoft Azure
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Data Storage, Integration & Security
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Azure Synapse Analytics & Databricks
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Azure Stream Analytics & Service Bus
Module 7: Apache Airflow
Module 8: PySpark & Big Data Processing
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Introduction to Apache Spark & PySpark
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PySpark SQL & DataFrames
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Kafka, Flume & Streaming with PySpark
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PySpark Machine Learning Basics
Module 9: DevOps for Data Engineers
Module 10: Power BI for Data Visualization
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Data Extraction, Transformation & Modeling
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Data Visualization & Analytics
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Power BI Cloud, Direct Connectivity & API Integration
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Power BI Premium & Advanced Features