Exploratory Data Analysis (EDA) for Machine Learning
Self-paced video training — 7 modules, 7 lessons. Work through it at your own pace — every lesson is real recorded training, not slide-reading.
▶INSIDE THE COURSE · 7 LESSONSABOUT THIS COURSE
This intermediate course focuses on Exploratory Data Analysis (EDA) as a foundational step in the machine learning process. Students will learn to understand and analyze data through univariate and bivariate analysis techniques, enabling them to uncover patterns, relationships, and insights. By the end of the course, participants will be equipped to apply EDA methods effectively to prepare data for machine learning models.
CURRICULUM
7 modules, in order.
01Introduction to EDA (Exploratory Data Analysis)1 LESSONS
this lesson introduces the concept of exploratory data analysis.
02Understanding the data1 LESSONS
this lesson focuses on how to understand the data for analysis.
03Univariate Analysis1 LESSONS
this lesson covers techniques for univariate analysis.
04Bivariate Analysis1 LESSONS
this lesson explores methods for bivariate analysis.
05Missing Values Treatments1 LESSONS
this lesson discusses how to treat missing values in data.
06Outliers Treatment1 LESSONS
this lesson focuses on methods for treating outliers in data.
07Variable Transformation1 LESSONS
this lesson examines techniques for variable transformation.
CURATED BY
Selected from experienced educators' training libraries and kept whole — modules, worked examples and walkthroughs exactly as taught.
GOOD TO KNOW
Lessons stream in the browser and remember where you stopped.
Watch on two devices at once — phone, tablet or desktop.
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$39 · ONE PAYMENT
Own every lesson, for life.
One payment unlocks all 7 lessons instantly — start with lesson one the moment you check out.