NumPy for Data Science

NumPy for Data Science, available at Free, has an average rating of 4.25, with 14 lectures, 7 quizzes, based on 78 reviews, and has 4894 subscribers.

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You will learn about You will learn about one of the most widely used Python libraries namely NumPy. I will teach everything right from the basics to advance level. This course is ideal for individuals who are Beginner developers who are interested in Python and want to specialize in the field of Data Science. It is particularly useful for Beginner developers who are interested in Python and want to specialize in the field of Data Science.

Enroll now: NumPy for Data Science

Summary

Title: NumPy for Data Science

Price: Free

Average Rating: 4.25

Number of Lectures: 14

Number of Quizzes: 7

Number of Published Lectures: 14

Number of Published Quizzes: 7

Number of Curriculum Items: 21

Number of Published Curriculum Objects: 21

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

You will learn about one of the most widely used Python libraries namely NumPy.

I will teach everything right from the basics to advance level.

Who Should Attend

Beginner developers who are interested in Python and want to specialize in the field of Data Science.

Target Audiences

Beginner developers who are interested in Python and want to specialize in the field of Data Science.

Welcome!

Data Science is one of the most trending fields in Computer Science and it is expected to grow exponentially in the coming years.

NumPy is one of the most used Python libraries in the field of Data Science.

In this course, we would slide through the various functions and properties that the Numpy library has to offer us. The primary things that we are going to learn are : 

Converting Simple Array to NumPy Array.

Generate a NumPy Array.

Methods used NumPyArrays.

Indexing and Comparison.

Selection and Copy.

Mathematical Functions and Operations.

Input and Output operations.

By the end of this course, you would be able to use the NumPy library with ease and perform various computing operations.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Intro to NumPy

Chapter 2: Importing and using package

Lecture 1: Importing Packages

Lecture 2: Modules vs Packages

Chapter 3: Generate NumPy Arrays

Lecture 1: Methods to generate NumPy Arrays

Lecture 2: Summary

Chapter 4: Functions in NumPy Arrays

Lecture 1: Mathematical functions in NumPy Arrays -1

Lecture 2: Mathematical functions in NumPy Arrays -2

Lecture 3: Mathematical Functions

Chapter 5: Indexing and Selection in NumPy Arrays

Lecture 1: Indexing and Selection

Chapter 6: Input Output using NumPy

Lecture 1: Input and Output

Lecture 2: Saving formats

Chapter 7: End

Lecture 1: Last lecture but First step

Lecture 2: Resources

Instructors

Suraj Verma
Developer & Programmer

Rating Distribution

1 stars: 2 votes

2 stars: 1 votes

3 stars: 11 votes

4 stars: 26 votes

5 stars: 38 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?

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