Foundations of Data Science
Master the essential skills and concepts needed before diving into Data Science.
Before stepping into the world of Data Science, it's crucial to build a strong foundation. This topic covers all the prerequisite knowledge you need — from mathematics and statistics to programming and data handling — so you can confidently move forward into machine learning, AI, and advanced analytics. Whether you're a complete beginner or brushing up your skills, this is your starting point.
What You'll Learn
Descriptive Statistics
Mean-Median-Mode
Mean, Median, and Mode are the three core measures of central tendency that every Data Scientist mu…
29 minWhat is Descriptive Statistics?
Descriptive statistics summarises and describes data so you can understand it at a glance. Learn wh…
12 minWhat is Variance?
Variance measures how far each value in a dataset is spread from the mean. Learn what it is, how to…
9 minTypes of Data — Nominal, Ordinal, Interval and Ratio Explained
Understanding data types is the most fundamental skill in statistics. Learn the four types of data …
9 minWhat is Standard Deviation?
Standard deviation is the square root of variance and measures spread in the same unit as your data…
11 minQuartiles, IQR and Outlier Detection
Learn what quartiles and the Interquartile Range (IQR) are, how to calculate them step by step, and…
17 minUnderstanding Box Plots
A box plot is a visual summary of quartiles, IQR and outliers in a single chart. Learn how to read,…
19 minWhat is Correlation
Learn what correlation means in statistics, how to calculate Pearson and Spearman coefficients, avo…
20 minCovariance Explained — What It Measures, Formula & Examples
Learn what covariance measures, how to calculate it step by step, and how it differs from correlati…
10 minKurtosis Explained — Leptokurtic, Platykurtic & Mesokurtic
Understand kurtosis from the ground up — what fat tails really mean, how to tell leptokurtic from p…
17 minCoefficient of Variation (CV)
Learn how the Coefficient of Variation (CV) lets you compare variability across datasets with diffe…
20 minInferential Statistics
Inferential Statistics
Inferential Statistics
A complete beginner-to-intermediate guide to inferential statistics — covering what inference means…
37 minEstimation Theory
A complete guide to estimation theory in statistics — covering point vs interval estimation, how co…
32 minHypothesis Testing, Null vs Alternative Hypothesis,
A complete guide to hypothesis testing — from the courtroom analogy that explains the core logic, t…
36 minThe p-value Explained
A deep-dive into the p-value — from the 1919 Lady Tasting Tea experiment that invented it, to a vis…
39 minOne-Tailed vs Two-Tailed Tests
A story-driven tutorial explaining the difference between one-tailed and two-tailed hypothesis test…
22 minTest Statistics Explained: Z, T, and Chi-Square
A comprehensive, story-driven tutorial covering the three essential test statistics — Z, T, and Chi…
26 minSignificance Level (α)
A deep, story-driven tutorial on the significance level α — covering its origin with Ronald Fisher,…
26 minType I & Type II Errors Explained
A richly illustrated, story-driven tutorial on Type I and Type II errors in hypothesis testing — co…
28 minProbability
Probability
Basic Probability Foundations
A comprehensive, story-driven tutorial covering the complete foundations of probability — from samp…
41 minConditional Probability
A deeply comprehensive, story-driven tutorial on conditional probability — covering P(A|B) = P(A∩B)…
36 minRandom Variables Explained: Discrete vs Continuous
A comprehensive, story-driven tutorial on random variables covering the discrete vs continuous spli…
45 minJoint & Marginal Probability
A richly illustrated, story-driven tutorial covering joint probability P(A,B), marginal probability…
43 minLikelihood & Maximum Likelihood Estimation
A comprehensive, story-driven tutorial on the likelihood function and MLE — covering probability vs…
39 min