Foundations of Data Science slides

Build a strong foundation in Data Science with essential concepts from statistics, probability, and data analysis. Learn the core knowledge needed to confidently progress toward Machine Learning, AI, and advanced analytics.

Start Learning 10 tutorials  ·  1 sections

Build a strong foundation before diving into Data Science and Machine Learning.
Learn essential concepts in descriptive and inferential statistics.
Understand probability, random variables, conditional probability, and likelihood.
Master concepts such as variance, correlation, hypothesis testing, p-values, and statistical errors.
Explore these concepts through beginner-friendly, practical, and story-driven tutorials.
Gain the confidence and mathematical foundation needed for Machine Learning, AI, and advanced analytics.

What You'll Learn

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Introduction

Mean, Median & Mode: The Three Faces of "Typical"

Three ways to answer one question — "what's the typical value?" The mean uses every number but bend…

38 min

What Is Descriptive Statistics? Centre, Spread & Shape

Before you predict anything, you have to describe what you have. Descriptive statistics compresses …

39 min

What Is Variance? Measuring the Spread Around the Mean

The average is only half the story. Variance measures how far values scatter from the mean — the nu…

35 min

Nominal, Ordinal, Interval & Ratio: The Four Types of Data

Before any statistic makes sense, you have to know what kind of number you're holding. Stevens' fou…

36 min

What Is Standard Deviation?

Variance in units you can read. Standard deviation answers "on average, how far is each value from …

36 min

Quartiles, IQR & Outlier Detection: The Robust Toolkit

Split sorted data into four equal parts, measure the middle 50%, and let a simple fence flag what d…

36 min

Understanding Box Plots: Read a Whole Distribution at a Glance

One compact chart that shows a dataset's centre, spread, skew, and outliers all at once. This tutor…

34 min

What Is Correlation? Strength, Direction & the Causation Trap

One number from −1 to +1 that captures how two variables move together — the sign is direction, the…

41 min

Covariance Explained: What It Measures, Formula & Examples

The number behind correlation. Covariance answers one question — do two variables move together? — …

32 min

Kurtosis Explained: Leptokurtic, Platykurtic & Mesokurtic

The shape statistic that measures tail heaviness — how likely extreme values are, not how "pointy" …

33 min