Data Preparation & Feature Engineering

Overview

Learn how to collect, clean, and transform data to make it suitable for AI and machine learning applications.

Modules

  • Data Collection: Sourcing and importing data from various platforms.

  • Data Cleaning: Handling missing values, outliers, and inconsistencies.

  • Feature Engineering: Creating and selecting features to improve model performance.

  • Data Augmentation: Techniques to expand and enrich datasets.
Lessons  Resources 

Lessons

Build a strong foundation in artificial intelligence. Learn core concepts, historical breakthroughs, and the impact of AI across industries so you can speak the language of AI with confidence.

Data Collection and Importing

This module focuses on ways you can source and import data from various platforms.

 Start 

Data Cleaning Fundamentals

This module focuses on ways you can handle missing values, outliers, and inconsistencies.

 Start 

Preparing Data for AI Tools

This module focuses on ways you can use techniques to expand and enrich datasets.

 Start 

Resources

Enhance your learning experience with study tools that help you dive deeper, practice concepts, and stay engaged beyond the lessons.

Notebook LM Study Guide

Use an interactive notebook and mind map that allows you to chat, review, and explore lesson topics in real time. Ask questions, revisit concepts, and get instant answers as you study.

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Podcast

Listen to in-depth discussions that expand on lesson topics. Hear expert insights, practical examples, and real-world applications to reinforce what you’ve learned.

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