Using Python's Math, Science, and Engineering Libraries

By Larry Fritts

This course covers the following topics: Math, NumPy, SciPy, Matplotlib, Pandas, and SciKit-Image.

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5 hours

23 Lessons
5 Hands-On Labs

About the course

This course covers "Exam block #2: Math, Science, and Engineering Tools" for the certification exam: PCPP-32-1: Certified Professional in Python Programming 1 Certification

Topics, as called out in the exam syllabus, are:

Math: A basic tool for elementary evaluations
NumPy: A fundamental package for scientific computing
SciPy: An ecosystem for mathematics, science, and engineering
Matplotlib: A 2D plotting library producing publication-quality figures
Pandas: A library providing high-performance and data analysis tools
SciKit-image: A collection of algorithms for image processing

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Chapter 1 2 Lessons Getting Started 1:38

Course Introduction
0:44

About the Training Architect
0:54
Chapter 2 1 Lesson Environment Setup 7:23

Installing Python 3.8 on a Cloud Playground Server
7:23
Chapter 3 2 Lessons Simple Math Using the `math` Module 49:37

Common `math` Functions and Constants
19:37

Calculating the Circumference of a Circle For a List of Radii in Python
30:00 Hands-On Lab
Chapter 4 1 Lesson Using SciPy 3:02

Overview of SciPy
3:02
Chapter 5 4 Lessons Using NumPy 1:00:45

What are NumPy Arrays?
15:52

Reshaping a Numpy Array Into a Matrix
12:28

Math Operations on Arrays/Matrices
2:25

Create a Matrix From Three Arrays in Python
30:00 Hands-On Lab
Chapter 6 5 Lessons Using Pandas 1:14:09

Creating and Using DataFrame
10:08

Slicing and Dicing DataFrame
8:43

Creating Pivot Tables
3:21

Stats With Dataframes
6:57

Examine a Dataframe and Create a Pivot Table in Python
45:00 Hands-On Lab
Chapter 7 3 Lessons Using Matplotlib 1:13:11

What Makes a Good Chart?
1:14

Bar Plots, Histograms, and Scatter Plots
26:57

Creating Graphs with Matplotlib
45:00 Hands-On Lab
Chapter 8 4 Lessons Using SciKit-image 58:15

NumPy and Scikit-Image
4:48

Image Data Types
2:24

Transforming Images
6:03

Edit a Photo in Python
45:00 Hands-On Lab
Chapter 9 1 Lesson Final Steps 0:34

What's Next?
0:34

What are Hands-on Labs

What's the difference between theoretical knowledge and real skills? Practical real-world experience. That's where Hands-on Labs come in! Hands-on Labs are guided, interactive experiences that help you learn and practice real-world scenarios in real cloud environments. Hands-on Labs are seamlessly integrated in courses, so you can learn by doing.

Using Python's Math, Science, and Engineering Libraries

About the course

Lab Highlights

Course Introduction

About the Training Architect

Installing Python 3.8 on a Cloud Playground Server

Common `math` Functions and Constants

Calculating the Circumference of a Circle For a List of Radii in Python

Overview of SciPy

What are NumPy Arrays?

Reshaping a Numpy Array Into a Matrix

Math Operations on Arrays/Matrices

Create a Matrix From Three Arrays in Python

Creating and Using DataFrame

Slicing and Dicing DataFrame

Creating Pivot Tables

Stats With Dataframes

Examine a Dataframe and Create a Pivot Table in Python

What Makes a Good Chart?

Bar Plots, Histograms, and Scatter Plots

Creating Graphs with Matplotlib

NumPy and Scikit-Image

Image Data Types

Transforming Images

Edit a Photo in Python

What's Next?

What are Hands-on Labs

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