Sourceful VS PythonDataScienceHandbook

This might be a good place to start.

www.hackingwithswift.com has good free resources and also some paid. Good place to start ;)

Sometimes the documentation can feel incomplete… though sometimes there are some really helpful tutorials. Once place I’ve found good info is from WWDC. Another is from Paul Hudson on https://www.hackingwithswift.com

Check out these resources.

For example, Paul Hudson's Hacking with Swift has 100 days of Swift and 100 days of SwiftUI. The first 15 days are dedicated to basics of programming like learning about variables, dictionary, etc. maybe you can skip through those but I would still look into topics like extensions, protocols, etc.

iOS programming is really straightforward, and with the advent of Swift and SwiftUI, it is really accessible. I kicked around an idea last year, and managed to get quite a decent prototype together very quickly. It doesn't have the best documentation for the language and software development kits, but there are loads of resources on the internet (Hacking with Swift is a good place to start).

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/