Data Science Libraries in Python

categories: Technology, Science & Productivity

Data

Software

Data Analysis

SDG 8: Decent Work and Economic Growth

SDG 9: Industry, Innovation and Infrastructure

By the end of this course, you will be able to

Recognize the NumPy library, its functions and how it is used with Python, in addition to the Pandas Data Frames and how they are used to solve complex tasks and handling Excel Files.
Understand the characteristics of the matplotlib and seaborn for data visualizations, their functions, and how they are used to create solid data visualizations.
Identify the different types of data science libraries, their functions, importance and how to use them in comparison to other types of data.

Course details

3 h 10 m/12 lessons
Last updated: 31/12/2022
Course completion certificate

Course Content

Free lessons

Numpy

19 Minutes

Array Operation

24 Minutes

1. Data Science Libraries

Numpy

19 Minutes

Array Operation

24 Minutes

Pickle

12 Minutes

Pandas

15 Minutes

Data Frame 1

14 Minutes

Data Frame 2

18 Minutes

Matplotlib DataFrame

9 Minutes

Data Processing

10 Minutes

Matplotlib 1

11 Minutes

10.

Matplotlib 2

15 Minutes

11.

Bar Chart

15 Minutes

12.

Example

24 Minutes

About this course

The Data Scientist profession has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems. This series of five training courses is designed to teach you how to program with Python, how to create amazing data visualizations, and how to use Machine Learning with Python.

Course requirements and prerequisites

There are no requirements for this course. Your interest in the topic and your commitment to learning are all you need to achieve the utmost benefit from this course.