Python for Data Science: Introduction to NumPy for Multi-dimentional Data

Expected Duration
Lesson Objectives
Course Number
Expertise Level


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.

Expected Duration (hours)

Lesson Objectives

Python for Data Science: Introduction to NumPy for Multi-dimentional Data

  • Course Overview
  • identify the applications of NumPy
  • install NumPy and learn how to create basic NumPy arrays
  • create specialized NumPy arrays
  • describe how arrays of different shapes and sizes can be displayed
  • explore the different mathematical operations available when working with arrays
  • work with functions which apply to each element of an array
  • retrieve specific parts of an array using row and column indices
  • describe the options available when iterating over 1-dimensional and multi-dimensional arrays
  • perform reshape operations on arrays to visualize its contents in different ways
  • utilize NumPy to perform basic array manipulation
  • Course Number:

    Expertise Level