Learn about Statistics for ML with interactive visualizations and depth.
Course Modules
Descriptive Statistics
Master the foundations of data analysis with interactive visualizations. Learn Central Tendency, Spread, Outliers, and EDA techniques via Python code.
Inferential Statistics
Master the art of drawing conclusions from data. Learn the Central Limit Theorem, Hypothesis Testing, and Confidence Intervals using interactive demos.
Estimation Theory
Master the fundamental techniques of statistical estimation. Learn how to infer population parameters using Maximum Likelihood, MAP, and Method of Moments.
Regression Analysis
Master Regression Analysis: From Simple Linear Regression and Gauss-Markov intuition to Residual Analysis and Regularization with Go, Java, and Python.
Non-Parametric Methods
Master Non-Parametric Methods in statistics. Learn the Bootstrap Method, Kernel Density Estimation, and Rank-Based Statistics to perform robust data analysis.