Description
Data Engineering Project SQL, Python, Airflow, Docker, CI/CD is a course on building a complete data engineering pipeline from start to finish published by Udemy Online Academy. This is a hands-on course that guides individuals through building a complete data engineering pipeline from start to finish. The course covers essential tools and technologies used in modern data engineering and combines SQL for data querying, Python for scripting and transformations, Airflow for workflow orchestration, Docker for containerization, and CI/CD pipelines for automation and deployment. By working on a real project, individuals gain hands-on experience in designing, implementing, and managing scalable data workflows.
To advance, you need experience working with the tools and processes that feed data pipelines in real-world environments. This course provides you with hands-on, project-based learning with the following tools in PostgreSQL, Python, Docker, Airflow, Postman, SODA, and Github Actions. I will guide you through how to use these tools. The course emphasizes the development of real-world projects and demonstrates how these technologies work together to create reliable and efficient data pipelines. Upon completion of the course, students will develop the skills necessary to build, deploy, and manage data engineering projects from start to finish in professional environments.
What you will learn in Data Engineering Project SQL, Python, Airflow, Docker, CI/CD:
- Build Python scripts to extract data by interacting with APIs using Postman, load into a data warehouse, and transform (ELT)
- Using PostgreSQL as a data warehouse. Interacting with the data warehouse using psql and DBeaver
- Discover how to containerize data applications using Docker and make your data pipelines portable and scalable.
- Master the basics of orchestrating and automating your data workflows with Apache Airflow, an essential tool in data engineering.
- Understand how to perform unit, integration, and end-to-end (E2E) testing using a combination of pytest and Airflow DAG tests to validate your data pipelines.
- Run data quality tests using SODA to ensure your data meets business and technical requirements.
- Learn to automate deployment pipelines using GitHub Actions to ensure smooth and continuous integration and delivery.
- And…
Course specifications
- Publisher : Udemy
- Teacher : Matthew Schembri
- Language: English
- Level : All Levels
- Lectures : 66
- Duration : 5 hours and 12 minutes
Course topics
Data Engineering Project SQL, Python, Airflow, Docker, CI/CD Prerequisites
At least 8 GB of RAM, though 16 GB is better for smoother performance
Python, Docker & Git installation to run/access the code course
Basic Python & SQL knowledge will be required
Knowledge of Docker & CI/CD is a plus but not necessary
Pictures
Data Engineering Project SQL, Python, Airflow, Docker, CI/CD introduction video
Installation guide
After Extract, watch with your favorite Player.
Subtitle: English
Quality: 720p
The 2026/2 version has increased the number of lessons by 3 and the duration increased by 2 minutes compared to 2025/8.
Download link
File password (s): www.downloadly.ir
Size
2.01 GB
