This book is edited by Li Hui and Chen Yanyan, with associate editors Yang Yu, Gao Yong, Zhang Qiaosheng, Bi Ye, and Liu Dengzhi. It is rich in content, covering 32 theories and 32 practical cases, ...

Python has become the most popular data science and machine learning programming language. But in order to obtain effective data and results, it’s important that you have a basic understanding of how ...

This online data science specialization is designed for learners with little to no programming experience who want to use Python as a tool to play with data. You will learn basic input and output ...

New extension pack bundles wildly popular tools for Python development, assisted by the AI-powered GitHub Copilot and a data wrangler.

Although Julia is purpose-built for data science, whereas Python has more or less evolved into the role, Python offers some compelling advantages to the data scientist.

Java has a lot going for it, but it's not the top language for data science. Java professionals may want to familiarize themselves with Python or R for data science workflows.

Students are constantly learning new analysis skills, and it can be easy to fall behind, get confused, or need a touch-up after a break from material. To help out, CADS has student interns devoted to ...

JetBrains has detailed its eighth annual Python Developers Survey. This survey is conducted as a collaborative effort between the Python Software Foundation and JetBrains’ PyCharm team.

What are some use cases for which it would be beneficial to use Haskell, rather than R or Python, in data science? This question was originally answered on Quora by Tikhon Jelvis.