Python NumPy For Your Grandma

Python NumPy For Your Grandma, available at Free, has an average rating of 4.75, with 44 lectures, based on 242 reviews, and has 10532 subscribers.

You will learn about NumPy for scientific computing in Python Create and manipulate NumPy Arrays Understand how to index multidimensional arrays (including 3+ dimensional arrays) Familiarization with numpy functions like stack(), argsort(), unique(), as_strided(), einsum() This course is ideal for individuals who are Python developers interested in scientific computing and data science It is particularly useful for Python developers interested in scientific computing and data science.

Enroll now: Python NumPy For Your Grandma

Summary

Title: Python NumPy For Your Grandma

Price: Free

Average Rating: 4.75

Number of Lectures: 44

Number of Published Lectures: 32

Number of Curriculum Items: 44

Number of Published Curriculum Objects: 32

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

NumPy for scientific computing in Python

Create and manipulate NumPy Arrays

Understand how to index multidimensional arrays (including 3+ dimensional arrays)

Familiarization with numpy functions like stack(), argsort(), unique(), as_strided(), einsum()

Who Should Attend

Python developers interested in scientific computing and data science

Target Audiences

Python developers interested in scientific computing and data science

Wanna learn NumPy?

Look no further. This course covers everything from how to install and import NumPy to how to solve complex problems involving array creation, transformations, and random sampling.

Course Structure

The course is presented as a series of on-demand lecture style videos with lots of animated examples, code walkthroughs, and challenge problems to test your knowledge. Go as fast or as slow as you want.

Philosophy

The course has a heavy emphasis on understanding NumPy, as opposed to rote memorization. But don’t take my word for it. Check out the free lecture videos in the course curriculum below!

Course Curriculum

Chapter 1: Course Introduction

Lecture 1: 1.1 Introduction

Lecture 2: PLEASE READ!

Chapter 2: Basic Array Stuff

Lecture 1: 2.1 NumPy Array Motivation

Lecture 2: 2.2 NumPy Array Basics

Lecture 3: 2.3 Creating NumPy Arrays

Lecture 4: 2.4 Indexing 1-D Arrays

Lecture 5: 2.5 Indexing Multidimensional Arrays

Lecture 6: 2.6 Basic Math On Arrays

Lecture 7: 2.7 Challenge: High School Reunion

Lecture 8: 2.8 Challenge: Gold Miner

Lecture 9: 2.9 Challenge Chic-fil-A

Chapter 3: Intermediate Array Stuff

Lecture 1: 3.1 Broadcasting

Lecture 2: 3.2 newaxis

Lecture 3: 3.3 reshape()

Lecture 4: 3.4 Boolean Indexing

Lecture 5: 3.5 nan

Lecture 6: 3.6 infinity

Lecture 7: 3.7 random

Lecture 8: 3.8 Challenge: Love Distance

Lecture 9: 3.10 Challenge: Psycho Parent

Chapter 4: Common Operations

Lecture 1: 4.1 where()

Lecture 2: 4.2 Math Functions

Lecture 3: 4.3 all() and any()

Lecture 4: 4.4 concatenate()

Lecture 5: 4.5 Stacking

Lecture 6: 4.6. Sorting

Lecture 7: 4.7 unique()

Lecture 8: 4.8 Challenge: Movie Ratings

Lecture 9: 4.9 Challenge: Big Fish

Chapter 5: Advanced Array Indexing

Lecture 1: 5.1 Advanced Array Indexing

Lecture 2: 5.2 View vs Copy

Lecture 3: 5.6 Challenge: Peanut Butter

Instructors

Ben Gorman
Data Scientist

Rating Distribution

1 stars: 1 votes

2 stars: 7 votes

3 stars: 22 votes

4 stars: 85 votes

5 stars: 127 votes

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!