This Skillsoft Aspire course explores NumPy, a Python library used in data science and big data. NumPy provides a framework to express data in the form of arrays; it supplies several array-based operations, and is the fundamental building block for several other Python libraries. For this course, you will need to know basics of programming in Python3, and should also have some familiarity in working with Jupyter notebooks, a browser-based interactive development environment to execute and view results without having to run the entire application. Learners will create an array and explore some of the basic operations, mostly mathematical ones, which can be performed on NumPy arrays. Next, learn to modify NumPy arrays, and then learn more complex operations, such as indexing and slicing, universal functions, and reshaping arrays. You will examine universal functions, which are NumPy library functions, which operate on an element-by-element basis on NumPy arrays. Finally, you will explore various options which are available, to iterate through arrays in NumPy.
Python for Data Science: Introduction to NumPy for Multi-dimentional Data