DataScienceWithPython
Get started with Data Science with Python
An engaging journey to become a Data Scientist with Python
TL;DR
- Download all Jupyter Notebooks from repo (zip-file-download).
- Unzip download (main.zip) an appropriate place.
- Launch Ananconda and start JuPyter Notebook (Install it from here if needed)
- Open the first Notebook from download.
- Start watching the first video lesson (YouTube).
Why do most fail with Data Science?
- Most focus on getting good at all technical aspects:
- Math
- Stat
- Python
- R
- Machine Learning
- pandas
- NumPy
- PyTorch
...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!
Master the Data Science Workflow
- 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!
What will we cover?
- 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
- Acquire - Prepare - Analyze - Report - Actions