Python NumPy Full Course (2024)

Python NumPy Full Course (2024), available at $19.99, has an average rating of 4.75, with 24 lectures, 6 quizzes, based on 8 reviews, and has 173 subscribers.

You will learn about Learn NumPy for Data Science (2024) Learn NumPy from scratch Acquire essential NumPy skills for numeric and scientific computing Be able to program in NumPy professionally. Practice your skills with 70+ exercises Learn NumPy best practices This course is ideal for individuals who are Get started with NumPy or Those who want to learn NumPy by doing. This course includes 50+ hands-on exercises or Gain a deep understanding of Python NumPy or Python Libraries Beginners It is particularly useful for Get started with NumPy or Those who want to learn NumPy by doing. This course includes 50+ hands-on exercises or Gain a deep understanding of Python NumPy or Python Libraries Beginners.

Enroll now: Python NumPy Full Course (2024)

Summary

Title: Python NumPy Full Course (2024)

Price: $19.99

Average Rating: 4.75

Number of Lectures: 24

Number of Quizzes: 6

Number of Published Lectures: 24

Number of Published Quizzes: 6

Number of Curriculum Items: 30

Number of Published Curriculum Objects: 30

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Learn NumPy for Data Science (2024)
Learn NumPy from scratch
Acquire essential NumPy skills for numeric and scientific computing
Be able to program in NumPy professionally.
Practice your skills with 70+ exercises
Learn NumPy best practices

Who Should Attend

Get started with NumPy
Those who want to learn NumPy by doing. This course includes 50+ hands-on exercises
Gain a deep understanding of Python NumPy
Python Libraries Beginners

Target Audiences

Get started with NumPy
Those who want to learn NumPy by doing. This course includes 50+ hands-on exercises
Gain a deep understanding of Python NumPy
Python Libraries Beginners

Welcome to The Complete NumPy Tutorial by Studyopedia.

NumPy is an open-source Python library, that allows you to work with multi-dimensional arrays and matrices, with the mathematical functions operating on these arrays. It stands for Numerical Python and is written in Python and C. It is a Python library for numeric and scientific computing. It consists of multi-dimensional array objects. It is faster with less LOC.

Python NumPy is considered one of the most powerful and top libraries for Data Science. In this course, we have covered over 70 examples to explain every concept of NumPy.

Numpy allows you to perform various operations on Arrays, including

Array Slicing
Array Join
Array Split
Array Reshape
Array Indexing
Array Search

Course Lessons

NumPy Introduction
Installing NumPy with pip
Create NumPy arrays
Dimensions in NumPy Arrays
Initialize NumPy Arrays
Datatypes in NumPy
NumPy Array Indexing
NumPy Array Slicing
NumPy Array Shape
Reshape a NumPy array
Iterate NumPy Arrays
Joining NumPy Arrays
Split NumPy Array
Search an Array for a value
Sorting NumPy Arrays
Axes in NumPy arrays
Intersection of NumPy Arrays
Difference between NumPy arrays
Arithmetic Operations on NumPy arrays
Scalar operations on NumPy arrays
Statistical Operations on NumPy arrays
Random module in NumPy
NumPy Logs
NumPy LCM and HCF

Quiz

We have also provided 6 Online Quizzes to polish your NumPy skills after completing the lessons.

100+ live coding examples are covered to make each lesson easier for the students.

Hit the Enroll button!

Course Curriculum

Chapter 1: NumPy – Introduction & Setup

Lecture 1: NumPy Introduction & Features

Lecture 2: Install NumPy (Set Environment)

Chapter 2: NumPy – Basics

Lecture 1: Create NumPy Arrays

Lecture 2: Dimensions in NumPy Arrays

Lecture 3: Initialize NumPy Arrays

Lecture 4: NumPy DataTypes

Chapter 3: NumPy – Indexing and Slicing

Lecture 1: NumPy Array Indexing

Lecture 2: NumPy Array Slicing

Chapter 4: NumPy – Shape, Reshape, Iterate

Lecture 1: Array Shape

Lecture 2: Reshape a NumPy Array

Lecture 3: Iterate a NumPy Array

Chapter 5: NumPy – Join, Split, Search, Sort

Lecture 1: Join NumPy Arrays

Lecture 2: Split NumPy Arrays

Lecture 3: Search a NumPy Array for a value

Lecture 4: Sort NumPy Arrays

Lecture 5: Axes in NumPy Arrays

Chapter 6: NumPy – Operations

Lecture 1: Intersection of NumPy Arrays

Lecture 2: Difference between NumPy Arrays

Lecture 3: Arithmetic Operations on NumPy arrays

Lecture 4: Scalar Operations on NumPy arrays

Lecture 5: Statistical Operations on NumPy arrays

Chapter 7: NumPy – Miscellaneous

Lecture 1: Random module in NumPy

Lecture 2: NumPy Logs

Lecture 3: NumPy LCM and HCF

Instructors

Studyopedia Trainings
Studyopedia Team

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4 stars: 2 votes
5 stars: 6 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!

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