Python Project for Data Engineering
Master real-world data workflows with this comprehensive Python data engineering project course. Designed for aspiring and professional data engineers alike, this course guides you through building scalable ETL pipelines, integrating multiple data sources, and deploying production-ready systems using the Python ecosystem. You’ll gain hands-on experience with tools like Pandas, SQLAlchemy, Airflow, and cloud services for end-to-end data engineering workflows.
What You’ll Learn
- Designing scalable ETL pipelines using Python
- Data extraction from APIs, databases, and files
- Data transformation using Pandas and custom functions
- Automating workflows with Apache Airflow
- Storing and managing data with PostgreSQL and SQLAlchemy
- Using cloud storage like AWS S3 or Google Cloud Storage
- Monitoring and logging production data workflows
Requirements
- Intermediate Python programming skills
- Basic understanding of SQL and relational databases
- Familiarity with data manipulation libraries (Pandas preferred)
Course Description
This Python data engineering project course is built around a real-world data pipeline scenario. You’ll walk through the development of an end-to-end system—from data ingestion and cleaning, to transformation and loading—automated through scheduled workflows.
You’ll begin by setting up your local environment and exploring various data sources. Next, you’ll build modular Python scripts to extract, clean, and process datasets before storing them in a database. As your pipeline grows, you’ll integrate Apache Airflow to schedule and manage workflow dependencies. Finally, you’ll deploy your solution using cloud-based tools to simulate a production-grade environment.
By completing this project, you’ll demonstrate your ability to architect, build, and deploy scalable data pipelines—skills that are in high demand across industries.
About the Instructor
This project is developed by experienced data engineers with backgrounds in enterprise data platforms, cloud infrastructure, and large-scale data transformation systems. Their industry experience ensures the course mirrors real-world challenges and expectations.
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- ETL with Python
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