Lecture Notes on Fundamental of Data Analysis

This Jupyter Book contains lecture notes for the Fundamentals of Data Analysis Course, taught at the University of Catania by Prof. Antonino Furnari.

The notes are informal and meant to be used as teaching material - they may contain errors.

To point out any mistake, you can open an issue. Introductory slides to this course are available here.

Lecture 1

• 1. Introduzione ai laboratori e Installazione dell’Ambiente di Lavoro
• 2. Introduzione a Python

Lecture 2

• 3. Introduction to Data Analysis and Key Concepts
• 4. Probability for Data Manipulation

Lecture 3

• 5. Probability Distributions
• 6. Basic Elements of Information Theory

Laboratory 1

• 7. Introduzione a Numpy
• 8. Introduzione a Matplotlib
• 9. Introduzione a Pandas

Lecture 4

• 10. Misure di Frequenze e Rappresentazione Grafica dei Dati
• 11. Misure di Tendenza Centrale, Dispersione e Forma

Lecture 5

• 12. Associazione tra Variabili

Laboratory 2

• 13. Laboratorio su Misure di Frequenze e Rappresentazione Grafica dei Dati
• 14. Laboratorio su Misure di Tendenza Centrale, Dispersione e Forma
• 15. Associazione tra Variabili

Lecture 6

• 16. Statistical Inference

Lecture 7 & 8

• 17. Linear Regression

Lecture 9

• 18. Logistic Regression

Lecture 10

• 19. Causal Data Analysis

Laboratory 3

• 20. Laboratory on Statistical Inference
• 21. Laboratorio su Regressione Lineare
• 22. Laboratorio su regressione logistica

Lecture 11

• 23. Data as N-Dimensional Points
• 24. Clustering

Lecture 12

• 25. Density Estimation

Lecture 13

• 26. Principal Component Analysis

Laboratory 4

• 27. Exploratory/Inferential Analysis on the Heart Disease Dataset

Lecture 14

• 28. Introduction to Predictive Modelling and Regression Models

Lecture 15

• 29. Classification Task and Evaluation Measures
• 30. Discriminative Models for Classification

Lecture 16

• 31. Generative Models for Classification

Laboratory 5

• 32. Clustering, Density Estimation, and Principal Component Analysis
• 33. Clustering

Laboratory 6

• 34. Linear Regression from a Predictive Perspective
• 35. Classificazione