How to Build Data Pipelines for ML Projects with Python Code

Learn how to build data pipelines for machine learning projects in this 23-minute video tutorial. Explore key concepts in data engineering, including the differences between ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) pipelines. Discover techniques for extracting, transforming, and loading data, as well as orchestrating pipeline workflows. Follow along with a practical example using Python code to pull transcripts from YouTube videos. Gain insights into full-stack data science and prepare for the next steps in your machine learning journey.

Introduction -
Data Engineering -
Data Pipelines -
2 Types of Pipelines ETL vs ELT -
Extract -
Transform -
Load -
Orchestration -
Example Code: ETL of My YouTube Video Transcripts -
What's Next? -