Description
Python, Databricks & Apache Spark: Complete ETL Engineering is a course on how to design and build scalable ETL (extract, transform, load) pipelines for modern data platforms published by Udemy Online Academy. This is a comprehensive course that teaches you how to design and build scalable ETL (extract, transform, load) pipelines for modern data platforms. The course focuses on using Python with Apache Spark inside Databricks to efficiently process large datasets, transform raw data into formats ready for analysis, and deliver reliable data products. Learners gain hands-on experience with distributed data processing, cloud-based data engineering workflows, and best practices for building robust, production-grade ETL solutions.
Python is one of the most powerful and widely used programming languages in data engineering and analytics. Its rich ecosystem, including libraries like Pandas, PySpark, and NumPy, allows you to efficiently process data, automate workloads, and build scalable ETL systems. You’ll gain the skills to clean, transform, validate, and analyze large datasets, along with problem-solving techniques to tackle real-world ETL challenges – giving you a competitive edge in the data engineering field.
What you will learn in Python, Databricks & Apache Spark: Complete ETL Engineering:
- Perform customer distribution analysis, vendor metrics, and product classification
- Set up, navigate, and manage the Databricks workspace and user interface
- Understand how Databricks works and why it is a leader in modern data engineering
- Work confidently with Databricks notebooks, files, and compute clusters
- Improve development speed with productivity shortcuts and essential notebook commands
- Learn the Lakehouse architecture and Medallion data design pattern (Bronze-Silver-Gold)
- Master Delta Lake principles, including ACID transactions and Delta Log operations
- Use Unity Catalog for centralized management, permissions, and data organization
- Create and manage catalogs, schemas, tables, and volumes
- And more…
Course specifications
Publisher: Udemy
Instructors: Oak Academy and OAK Academy Team
Language: English
Level: Introductory to Advanced
Number of Lessons: 168
Duration: 23 hours and 35 minutes
Course topics
Python, Databricks & Apache Spark: Complete ETL Engineering Prerequisites
A working computer (Windows, Mac, or Linux)
A stable internet connection to access Databricks
Basic understanding of SQL (basic queries like SELECT, WHERE, JOIN are enough)
Interest in data engineering and real-world data pipelines
Curiosity about modern cloud platforms and large-scale ETL workflows
Motivation to build complete end-to-end pipelines using Databricks & Apache Spark
No prior experience with Databricks, Spark, or the Lakehouse required
Just you, your keyboard, and your passion for becoming a data engineer!
Pictures
Python, Databricks & Apache Spark: Complete ETL Engineering introduction video
Installation guide
After Extract, watch with your favorite Player.
Subtitle: None
Quality: 1080p
Downloadly link
Rapidgator link
File password (s): www.downloadly.ir
Size
8.8 GB
