Welcome to the official EasyPass Coding Crashcourse! Coding is not easy and definitely not intuitive at first. This compilation of notebooks provides an interactive overview of essential concepts and helps you to familiarize yourself with some of the core concepts around programming basics, data science, data visualization and machine learning.

Table of Contents

Basics of Python

Introduction
Running Python Code
Python Syntax
Python Semantics: Variables & Objects
Python Semantics: Operators
Data Types: Scalars
Data Types: Data Structures
Data Types: Type Conversion
Control Flow
Functions
Errors and Exceptions
Iterators
Modules and Packages
String Manipulation
Input and Output
Functional Programming

Object Oriented Programming

What is Object Oriented Programming?

Data Science: SQL

Basics of Relational Databases
SELECT Statement
WHERE Clause
GROUP BY Clause
ORDER BY Clause
LIMIT Clause
Merging Databases: JOIN
Manipulating Databases: INSERT, INTO, DELETE
SQL in Python

Data Science: Numpy

Introduction to Numpy
Understanding Arrays
Arrays in Numpy
Aggregations
Broadcasting
Sorting Arrays

Data Science: Pandas

Data Wrangling with Pandas
Series and DataFrames
Data Indexing and Selecting
Operations in DataFrames
Handling Missing Values
Merging DataFrames
Aggregation and Grouping

Data Visualization

Why Data Visualization?
Matplotlib
Basics of Plotting
Line Graphs & Scatter Plots
Bar Charts
Subplots
Further Plots: Historgram, Boxplot & Heatmap
Plotting with Pandas

Machine Learning with Scikit-Learn

What is Machine Learning
Using Scikit-Learn
Model Validation and Hyperparameters

How to use this course

Above you can find a collection of interactive jupyter notebooks, covering material ranging from the basics of python to machine learning.

We strongly encourage you to focus on understanding rather than learning by heart. Therefore, feel free to run, adapt and experiment with the code to get the most out of it. Remember: Practice makes perfect!

Note: If you open our notebooks you can always edit the code without changing the original file, allowing you to practice by yourself. You can even save changes to your personal Google Drive.

To access/run the notebooks just click on the respective Google Colab links. If you get the warning “This notebook was not authored by Google” don’t worry, just press “Run Anyway”.

Licence

This collection is released under the “No Rights Reserved” CC0 license, and thus you are free to re-use, modify, build-on, and enhance this material for any purpose. Read more about CC0 here.

Sources

This collection of notebooks was created with the help of the following materials: