SkillSoft Explore Course – Lambers, Inc.

IT Skills Data and Databases Data Science Python for Data Science

This 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, 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. You will learn how to create NumPy arrays and perform basic mathematical operations on them. Next you will see how to modify, index, slice, and reshape the arrays; and examine the NumPy library's universal array functions that operate on an element-by-element basis. Conclude by learning how to iterate various options through NumPy arrays.

Asset ID	it_dspydsdj_01_enus
Course Type	Video Course
Course Category	Data and Databases

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

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