PythonDataScienceHandbook VS materials

Python Data Science Handbook

Python Data Science Handbook — learn to use Python libraries such as NumPy, Pandas, Matplotlib, Scikit-Learn, and related tools to effectively store, manipulate, and gain insight from data

I don't know what tools you will be using but if you will be using Python you can start with Python Data Science Handbook by Jake VanderPlas and Data Science & Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting DataData Science & Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data which gives a very good outlook on the data science and big data frame work. PS: Jake's book is also available as jupyter notebooks so you can read and run the code at the same time.

Python Data Science Handbook by Jake VanderPlas (https://jakevdp.github.io/PythonDataScienceHandbook/)

Otherwise you can work through courses on Datacamp, Coursera, Udemy, etc, or check out this book for a more general non-spatial perspective.

7. Data Science Handbook Are you looking for a comprehensive guide to data science with Python? Look no further than the Data Science Handbook by Jake VanderPlas. This repository contains the entire book, which introduces essential tools and techniques used in data science, including IPython, NumPy, Pandas, Matplotlib, and Scikit-Learn. It’s a fantastic resource for anyone looking to deepen their understanding of data science concepts and best practices.

I can recommend https://jakevdp.github.io/PythonDataScienceHandbook/

Python - Python.org - Official Python website with documentation and tutorials. - Codecademy Python Course - Real Python - Python tutorials and articles for all skill levels.

I am no expert on facial recognition software but I read over an article on https://realpython.com. The site might be a little pricey (to some) but a few people in my Python group highly recommended it. It does have a ton of good tutorials.

Real Python

https://realpython.com/ is an excellent source. You can find there the building blocks of Python, explanations, hints, and tips.

Check out RealPython they were a great resource for me when I first started with Python. Linux skills will always be in demand too, though you might not necessarily find a job for both Python and Linux but I'm sure many exist. When you build a project make sure to document it and have a GitHub page for it, in a way your GitHub will serve as your resume in the software engineering space so take time to learn the platform and Git. More than likely you will also use GitHub or another VCS on the job so it's worth trying to understand.

Website: Real Python - Free docs are good

For help on specific topics, courses, or crash course style articles on a topic/technique, check out https://realpython.com/