Feature
Engineering
45 Lessons · 3 Levels
Transform raw data into powerful predictive signals — from encoding and scaling to advanced lag features, deep feature synthesis and ML-based selection techniques.
45Lessons
3Levels
1Projects
FreeAccess
Level I
Beginner Level
Lessons 1–15
Lesson 01
Introduction to Feature Engineering
Lesson 02
What Are Features?
Lesson 03
Types of Features
Lesson 04
Numerical Features
Lesson 05
Categorical Features
Lesson 06
Date & Time Features
Lesson 07
Text Features Basics
Lesson 08
Missing Data
Lesson 09
Outliers
Lesson 10
Data Transformations
Lesson 11
Binning & Discretization
Lesson 12
Feature Scaling
Lesson 13
Encoding Basics
Lesson 14
Feature Construction
Lesson 15
FE Workflow
Level II
Intermediate Level
Lessons 16–35
Lesson 16
Polynomial Features
Lesson 17
Interaction Features
Lesson 18
Target Encoding
Lesson 19
Frequency Encoding
Lesson 20
Weight of Evidence
Lesson 21
Rare Label Encoding
Lesson 22
Outlier-Based Features
Lesson 23
Transformations for Skewed Data
Lesson 24
Feature Selection Basics
Lesson 25
Filter Methods
Lesson 26
Wrapper Methods
Lesson 27
Embedded Methods
Lesson 28
Variance Thresholding
Lesson 29
Missing Indicator Features
Lesson 30
Domain-Driven Features
Lesson 31
Advanced DateTime Features
Lesson 32
Group-Based Features
Lesson 33
Rolling Window Features
Lesson 34
Lag Features
Lesson 35
FE for Imbalanced Data
Level III
Advanced Level
Lessons 36–45