Python For Machine Learning (ML) Course

Course Instructor:

Fabio Mardero is a data scientist from Italy. He graduated in physics and statistical and actuarial sciences. He is currently working at a well-known Italian insurance company as a data scientist and Non-Life technical provisions evaluator. 

Course Overview & Lectures

Duration: 14+ hours


Insurance Project

Italian COVID dataset (official data):

Insurance dataset:

1. Introduction to Python

Programming language features, VS Code, Jupyter Notebook/Lab (Colab), virtual environments, variables, data types, lists and dictionaries.

Lecture 1: General Overview

Lecture 2: Setup Python Project

Lecture 3: Venv (Virtual Environment)

Lecture 4: Git

Lecture 5: Python Tools and IDEs

Lecture 6: Data Types

2. If/else and Loops

If/else, loops, iterators and generators, error handling.

Lecture 7: Loops & If Else

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3. Functions and Classes

Functions, decorators, classes, inheritance, decorators inside classes.

Lecture 8: Class Function

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4. Pandas and Numpy

Arrays and Matrices, reading files, DataFrame, Series, pivot tables, group by, pipelines, datetime objects.

Lecture 9: Pandas Part 1

Lecture 10: Pandas Part 2

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5. Static Plotting

Static plots using matplotlib and seaborn libraries.

Lecture 11: Static Plotting

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6. Dynamic Plotting

Animations, dynamic plots using altair library

Lecture 12: Dynamic Plotting

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7. Unit Testing and Logging

File arrangement to build a Python library, assertions, Test Case (unittest library), logging (logging library)

Lecture 13: Unit Testing

Lecture 14: Logging

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8. Computer Vision


Lecture 15: Computer Vision

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