# A brief introduction to some of the scientific computing used in this course. In particular the NumPy scientific computing package and its use with python ...

Overview Structured Python learning path that moves from fundamentals (syntax, loops, functions) to real data science tools ...

Python is convenient and flexible, yet notably slower than other languages for raw computational speed. The Python ecosystem has compensated with tools that make crunching numbers at scale in Python ...

Python has many great advantages that leads to it being the programming language of choice for a large range of users. However, it is an inherently inefficient language and performing extensive ...

Python’s versatility, speed, and rich ecosystem of libraries have made it the go-to language for industries from data science ...

You may have heard about NumPy and wondered why it seems so essential to data analysis in Python. What makes NumPy seemingly end up everywhere in statistical calculations with Python? Here are some ...

[Zoltán] sends in his very interesting implementation of a NumPy-like library for micropython called ulab. He had a project in MicroPython that needed a very fast FFT on a micro controller, and was ...