DataScienceWithPython

Get started with Data Science with Python

An engaging journey to become a Data Scientist with Python

There are two options.

Download all the notebooks from this repository and run them in Jupyter Notebook. Chapter one in eBook will get you started with that.
Follow along using Google colab

Note: On each of those options, you'll find:

A starter folder, which contains all the notebooks, that are empty in order to follow along.
A final folder, which contains all the notebooks with all the source code.

No installations needed.
Go to Colab Notebooks Folder
Start watching the first video lesson (YouTube).
Note: On each notebook, click on "Open in Colab", in order to open it on Google Colab

...and the list could go on and we didn't dive into sub-categories (but you get the point)

DISCLAIMER!!! This is the wrong (long) way to learn!

Understanding what matters
- The full workflow
- How to add value to customers
Focus on how to add value
- This can be done with limited technical knowledge
- ...and we will cover all you need
Later you can become an expert in whatever your interest are
But you should first understand the WHY!

This course will cover all aspects of it with the focus to get you there as fast as possible!

Data Science Workflow
- Acquire - Prepare - Analyze - Report - Actions
Data Visualization
pandas for Data Science
Data Sources
- Web Scraping
- Databases
- CSV, Excel & parquet files
Where to find data
Join (combine) data
Statistics you need to know
Machine Learning Models
- Linear Regression
- Classification
- ...also check out the Machine Learning Course
Cleaning Data
Feature Scaling
Feature Selection
Model Selection

At the end of the course you are provided with a template covering all aspects of the Data Science Workflow