Top 10 numpy course for data analytics Best top numpy course

Top 10 numpy course for data analytics Best top numpy course, available at $19.99, with 25 lectures, and has 2 subscribers.

You will learn about Python numpy: The numerical array to store data Attributes of numpy and their usage Creation of array by using different routines Usage of numpy Use of numpy with matplotlib This course is ideal for individuals who are Under graduate, post graduate students, working professional, aspiring data analyst/scientist It is particularly useful for Under graduate, post graduate students, working professional, aspiring data analyst/scientist.

Enroll now: Top 10 numpy course for data analytics Best top numpy course

Summary

Title: Top 10 numpy course for data analytics Best top numpy course

Price: $19.99

Number of Lectures: 25

Number of Published Lectures: 25

Number of Curriculum Items: 25

Number of Published Curriculum Objects: 25

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Python numpy: The numerical array to store data
Attributes of numpy and their usage
Creation of array by using different routines
Usage of numpy
Use of numpy with matplotlib

Who Should Attend

Under graduate, post graduate students, working professional, aspiring data analyst/scientist

Target Audiences

Under graduate, post graduate students, working professional, aspiring data analyst/scientist

The data analytics needs specialized data structure for storing numerical data. The numpy library provides the required data stucture. NumPy is a Python package. It stands for ‘Numerical Python’. It is a library consisting of multidimensional array objects and a collection of routines for processing of array. In this course python numpy library is explained in details. In this tutorial you will learn,

What is numpy?
How to create and use numpy array?
Accessing elements of array.
Operations on numpy array.
Functions of numpy array.

Anybody knowing basic knowledge of python programming can take up this course. In this course each and every concept is explained in detail. Also following resources are provided to students,

Notes
Examples

The contents of this course are,

1. What is numpy

2. How to install numpy

3. NumPy – Ndarray Object

4. NumPy – Data Types

5. NumPy – Array Attributes

6. NumPy – Array Creation Routines

7. NumPy – Array From Existing Data

8. NumPy – Array From Numerical Ranges

9. NumPy – Indexing & Slicing

10. NumPy – Advanced Indexing

11. NumPy – Broadcasting

12. NumPy – Iterating Over Array

13. NumPy – Array Manipulation

14. NumPy – Binary Operators

15. NumPy – String Functions

16. NumPy – Mathematical Functions

17. NumPy – Arithmetic Operations

18. NumPy – Statistical Functions

19. NumPy – Sort, Search & Counting Functions

20. NumPy – Byte Swapping

21. NumPy – Copies & Views

22. NumPy – Matrix Library

23. NumPy – Linear Algebra

24. NumPy – Matplotlib

25. NumPy – Histogram Using Matplotlib

26. I/O with NumPy

Course Curriculum

Chapter 1: Introduction to numpy

Lecture 1: Introduction

Lecture 2: How to install numpy

Lecture 3: NumPy – Ndarray Object

Lecture 4: NumPy – Data Types

Lecture 5: NumPy – Array Attributes

Chapter 2: NumPy Array Creation

Lecture 1: NumPy – Array Creation Routines

Lecture 2: NumPy – Array From Existing Data

Lecture 3: NumPy – Array From Numerical Ranges

Chapter 3: Accessing numpy array

Lecture 1: NumPy – Indexing & Slicing

Lecture 2: NumPy – Advanced Indexing

Lecture 3: NumPy – Broadcasting

Lecture 4: NumPy – Iterating Over Array

Chapter 4: Operations on numpy array

Lecture 1: NumPy – Array Manipulation

Lecture 2: NumPy – Binary Operators

Lecture 3: NumPy – Mathematical Functions

Lecture 4: NumPy – Arithmetic Operations

Lecture 5: NumPy – Statistical Functions

Lecture 6: NumPy – Sort, Search & Counting Functions

Lecture 7: NumPy – Byte Swapping

Chapter 5: Advanced operations on numpy array

Lecture 1: NumPy – Copies & Views

Lecture 2: NumPy – Matrix Library

Lecture 3: NumPy – Linear Algebra

Lecture 4: NumPy – Matplotlib

Lecture 5: NumPy – Histogram Using Matplotlib

Lecture 6: I/O with NumPy

Instructors

Dr Karveer B Manwade
Professor

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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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