Projects-Solutions VS PythonDataScienceHandbook

karan/Projects-Solutions : Solutions to most of the problems in the link above

Projects with solutions — algorithms, data structures, networking, security, databases, etc

And try making some of these projects https://github.com/karan/Projects-Solutions

There's also a handy GitHub repo with project ideas and solutions: https://github.com/karan/Projects-Solutions

If you want to follow along projects as practice, check out resources like https://github.com/karan/Projects-Solutions and https://github.com/practical-tutorials/project-based-learning#python

Start doing projects, my man. Reading (by itself) a million books will not make you a Shakespeare. https://github.com/karan/Projects-Solutions/blob/master/README.md is a simple list - read the descriptions, pick one that you like, start implementing it. Post queries/code review requests here, and up your game.

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/