How to Build Data Pipelines for ML Projects with Python Code

Offered By: Shaw Talebi via YouTube

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!

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.

Syllabus

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? -

Taught by

Shaw Talebi

Related Courses

Introduction to Artificial Intelligence
Stanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent