Understanding the NumPy Mindset • Numerical Python

Understanding the NumPy Mindset • Numerical Python, available at $54.99, has an average rating of 4.61, with 27 lectures, based on 9 reviews, and has 101 subscribers.

You will learn about Learn the fundamentals of Python's NumPy package Understand the mindset needed to work with NumPy Learn to create and use NumPy's ndarray object Use NumPy in real-world examples This course is ideal for individuals who are Python programmers who are keen to learn about Python's key numerical programming package: NumPy It is particularly useful for Python programmers who are keen to learn about Python's key numerical programming package: NumPy.

Enroll now: Understanding the NumPy Mindset • Numerical Python

Summary

Title: Understanding the NumPy Mindset • Numerical Python

Price: $54.99

Average Rating: 4.61

Number of Lectures: 27

Number of Published Lectures: 27

Number of Curriculum Items: 27

Number of Published Curriculum Objects: 27

Original Price: $34.99

Quality Status: approved

Status: Live

What You Will Learn

Learn the fundamentals of Python's NumPy package
Understand the mindset needed to work with NumPy
Learn to create and use NumPy's ndarray object
Use NumPy in real-world examples

Who Should Attend

Python programmers who are keen to learn about Python's key numerical programming package: NumPy

Target Audiences

Python programmers who are keen to learn about Python's key numerical programming package: NumPy

This is a concise course that covers the fundamentals of Python’s NumPy package. Most students who learn NumPy for the first time say that it feels differentfrom the core Python they learnt. And they’re right.

NumPy requires a different mindset. There’s a reason why NumPy does things differently and if you understand why things are the way they are in NumPy, the rest of your NumPy journey will be easier.

This course doesn’t try to cover everything in the NumPy package. That’s impossible and not desirable. Instead, I designed this course to be concise and to focus on what really matters:

Understanding the core topics in NumPy
Understanding the NumPy mindset

This course covers the following topics:

NumPy’s main data structure, the ndarray
Vectorisation in NumPy
Arrays in higher dimensions
The basics of broadcasting
Filtering NumPy arrays using Boolean operations and Boolean indexing
Reading external data using NumPy
Representing equations with NumPy

And of course, throughout the whole course you’ll get familiar with the NumPy mindset.

—

About me, your instructor

I’ve been teaching Python and NumPy for a decade. Before that, I worked as a physicist and used numerical and scientific programming in my research work for over a decade.

My focus is on communicating clearly, in a friendly and relaxed manner. I’m the author of the The Python Coding Book (you can ask Google for a “python book” and you’ll find this book as one of the first entries) and I have taught Python to individuals and corporations around the world.

And I’m approachable. You can ask me questions and I’ll always reply, whether here on social media or anywhere else you can find me!

Course Curriculum

Chapter 1: On the Road to NumPy

Lecture 1: What's This Course About?

Lecture 2: Let's Start With Lists. Yes, Lists

Lecture 3: The Lesser-Known Array

Chapter 2: Understanding NumPy's `ndarray` Data Type

Lecture 1: Installing NumPy

Lecture 2: Finally, Say Hello to `ndarray`

Lecture 3: Looking Ahead to Some Other `ndarray` Features

Chapter 3: Vectorisation • A Fancy Word For NumPy's "Superpower"

Lecture 1: Performing Operations Element-by-Element in NumPy • Vectorisation

Lecture 2: Comparing Loops With Lists, List Comprehensions, and NumPy Vectorisation

Lecture 3: Let's Race • Timing The Three Versions

Lecture 4: A Glimpse At NumPy's Documentation

Chapter 4: Multiple Dimensions in NumPy Arrays

Lecture 1: More Than One Dimension

Lecture 2: Creating Arrays of Random Numbers • The Five-Player Three-Round Game

Lecture 3: Broadcasting • A Brief Introduction

Lecture 4: Another Glimpse At NumPy's Documentation

Lecture 5: Let's Add One More Dimension • 3D Arrays

Chapter 5: Boolean Operations, Boolean Indexing, Filtering, And More

Lecture 1: Boolean Operations on NumPy Arrays

Lecture 2: Boolean Indexing and Filtering

Lecture 3: There's Lots More in NumPy's API

Lecture 4: Views and Copies • A Brief Introduction

Chapter 6: The Met Office Temperature Dataset

Lecture 1: Reading The Data From a CSV File to a NumPy Array

Lecture 2: Remove What We Don't Need From The Array

Lecture 3: Finding the Minimum, Maximum, and Mean Temperatures

Lecture 4: Grouping Temperatures Using a Histogram

Lecture 5: Grouping Temperatures Using a Histogram • Plotting the Data

Chapter 7: Representing Equations Using NumPy

Lecture 1: From an Equation on Paper to An Equation on Computer • `np.arange()` and `np.lin

Lecture 2: Plotting The Equation

Lecture 3: Final Words

Instructors

Stephen Gruppetta
Python Educator

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Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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