Build & Transform Data Pipelines

Overview

Ready to build data pipelines that power modern analytics? This course transforms you from someone who processes data manually into a data engineer who creates automated, modular pipeline systems. This Short Course was created to help Data Management and Engineering professionals accomplish scalable, maintainable data processing workflows. By completing this course, you'll be able to design and implement production-ready pipelines that seamlessly move data from raw sources to analytics-ready destinations using industry-standard tools. By the end of this course, you will be able to: • Create modular pipeline stages for data ingestion, cleansing, transformation, and loading • Implement automated workflows using Python, dbt, and Airflow • Deploy scalable solutions on cloud platforms like AWS and Snowflake This course is unique because it focuses on hands-on implementation with real-world scenarios using popular open-source tools that drive today's data infrastructure. To be successful in this project, you should have a background in basic SQL, Python programming, and familiarity with data concepts.

Syllabus

Module 1: Modular Pipeline Development - Foundation & Core

Learners will establish the foundational understanding and core skills for creating modular data pipeline stages, focusing on the principles of separation of concerns and tool integration fundamentals.

Module 2: Pipeline Implementation & Integration - Application & Assessment

Learners will implement complete end-to-end data pipelines by integrating modular components with industry-standard tools, culminating in comprehensive assessment of their pipeline development capabilities.