This course is designed to equip learners with end-to-end data engineering skills using Python. You will learn how to collect, store, process, and transform large-scale data efficiently while building scalable data pipelines. The program covers Python programming, data processing frameworks, database management, cloud platforms, and hands-on projects to prepare you for real-world data engineering roles.
Module 1: Python for Data Engineering Python basics, data structures, and OOP Libraries: Pandas, NumPy, and Matplotlib.
Module 2: SQL & Relational Databases SQL queries, joins, subqueries, and indexing Database design and normalization.
Module 3: NoSQL Databases Introduction to MongoDB / Cassandra CRUD operations and data modeling.
Module 4: ETL Concepts Understanding ETL pipelines Data extraction, transformation, and loading techniques.
Module 5: Data Warehousing Introduction to Data Warehouses Star & Snowflake schema design Fact and Dimension tables.
Module 6: Big Data Processing with PySpark RDDs, DataFrames, and Spark SQL Transformations and Actions.
Module 7: Workflow Orchestration Apache Airflow fundamentals DAG creation, scheduling, and monitoring.
Module 8: Cloud Data Engineering Basics AWS S3, Redshift, and Lambda basics Data pipeline deployment.
Module 9: Real-Time Data Processing Kafka basics Streaming pipelines with PySpark.
Module 10: Industry Projects & Capstone Building end-to-end data pipelines Working with structured and unstructured data Real-world project deployment.
Mobile: 9100348679
Email: coursedivine@gmail.com
You cannot copy content of this page