Udemy

Platform

English

Language

Data Science

Category

100+ Exercises - Python Programming - Data Science - NumPy

Improve your Python programming and data science skills and solve over 100 exercises in NumPy!

4.39 (104 reviews)

Students

1 hour

Content

Sep 2021

Last Update
Regular Price


What you will learn

solve over 100 exercises in NumPy

deal with real programming problems in data science

work with documentation and Stack Overflow

guaranteed instructor support


Description

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RECOMMENDED LEARNING PATH

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COURSE DESCRIPTION

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100+ Exercises - Python Programming - Data Science - NumPy

Welcome to the course 100+ Exercises - Python Programming - Data Science - NumPy, where you can test your Python programming skills in data science, specifically in NumPy.


Some topics you will find in the exercises:

  • working with numpy arrays

  • generating numpy arrays

  • generating numpy arrays with random values

  • iterating through arrays

  • dealing with missing values

  • working with matrices

  • reading/writing files

  • joining arrays

  • reshaping arrays

  • computing basic array statistics

  • sorting arrays

  • filtering arrays

  • image as an array

  • linear algebra

  • matrix multiplication

  • determinant of the matrix

  • eigenvalues and eignevectors

  • inverse matrix

  • shuffling arrays

  • working with polynomials

  • working with dates

  • working with strings in array

  • solving systems of equations


The course is designed for people who have basic knowledge in Python and NumPy package. It consists of 100 exercises with solutions.

This is a great test for people who are learning the Python language and data science and are looking for new challenges. Exercises are also a good test before the interview. Many popular topics were covered in this course.


If you're wondering if it's worth taking a step towards Python, don't hesitate any longer and take the challenge today.


Screenshots

100+ Exercises - Python Programming - Data Science - NumPy
100+ Exercises - Python Programming - Data Science - NumPy
100+ Exercises - Python Programming - Data Science - NumPy
100+ Exercises - Python Programming - Data Science - NumPy

Content

Configuration (optional)

Info

Google Colab + Google Drive

Google Colab + GitHub

Google Colab - Intro

Anaconda installation - Windows 10

Introduction to Spyder

Anaconda installation - Linux

Tips

A few words from the author

Tip

Starter

Exercise 0

Solution 0

Exercises 1-10

Exercise 1

Solution 1

Exercise 2

Solution 2

Exercise 3

Solution 3

Exercise 4

Solution 4

Exercise 5

Solution 5

Exercise 6

Exercise 6

Exercise 7

Solution 7

Exercise 8

Solution 8

Exercise 9

Solution 9

Exercise 10

Solution 10

Exercises 11-20

Exercise 11

Solution 11

Exercise 12

Solution 12

Exercise 13

Solution 13

Exercise 14

Solution 14

Exercise 15

Solution 15

Exercise 16

Solution 16

Exercise 17

Solution 17

Exercise 18

Solution 18

Exercise 19

Solution 19

Exercise 20

Solution 20

Exercises 21-30

Exercise 21

Solution 21

Exercise 22

Solution 22

Exercise 23

Solution 23

Exercise 24

Solution 24

Exercise 25

Solution 25

Exercise 26

Solution 26

Exercise 27

Solution 27

Exercise 28

Solution 28

Exercise 29

Solution 29

Exercise 30

Solution 30

Exercises 31-40

Exercise 31

Solution 31

Exercise 32

Solution 32

Exercise 33

Solution 33

Exercise 34

Solution 34

Exercise 35

Solution 35

Exercise 36

Solution 36

Exercise 37

Solution 37

Exercise 38

Solution 38

Exercise 39

Solution 39

Exercise 40

Solution 40

Exercises 41-50

Exercise 41

Solution 41

Exercise 42

Solution 42

Exercise 43

Solution 43

Exercise 44

Solution 44

Exercise 45

Solution 45

Exercise 46

Solution 46

Exercise 47

Solution 47

Exercise 48

Solution 48

Exercise 49

Solution 49

Exercise 50

Solution 50

Exercises 51-60

Exercise 51

Solution 51

Exercise 52

Solution 52

Exercise 53

Solution 53

Exercise 54

Solution 54

Exercise 55

Solution 55

Exercise 56

Solution 56

Exercise 57

Solution 57

Exercise 58

Solution 58

Exercise 59

Solution 59

Exercise 60

Solution 60

Exercises 61-70

Exercise 61

Solution 61

Exercise 62

Solution 62

Exercise 63

Solution 63

Exercise 64

Solution 64

Exercise 65

Solution 65

Exercise 66

Solution 66

Exercise 67

Solution 67

Exercise 68

Solution 68

Exercise 69

Solution 69

Exercise 70

Solution 70

Exercises 71-80

Exercise 71

Solution 71

Exercise 72

Solution 72

Exercise 73

Solution 73

Exercise 74

Solution 74

Exercise 75

Solution 75

Exercise 76

Solution 76

Exercise 77

Solution 77

Exercise 78

Solution 78

Exercise 79

Solution 79

Exercise 80

Solution 80

Exercises 81-90

Exercise 81

Solution 81

Exercise 82

Solution 82

Exercise 83

Solution 83

Exercise 84

Solution 84

Exercise 85

Solution 85

Exercise 86

Solution 86

Exercise 87

Solution 87

Exercise 88

Solution 88

Exercise 89

Solution 89

Exercise 90

Solution 90

Exercises 91-100

Exercise 91

Solution 91

Exercise 92

Solution 92

Exercise 93

Solution 93

Exercise 94

Solution 94

Exercise 95

Solution 95

Exercise 96

Solution 96

Exercise 97

Solution 97

Exercise 98

Solution 98

Exercise 99

Solution 99

Exercise 100

Solution 100


Reviews

J
Jawad9 July 2021

The course is very good and I have learned a lot from the exercises. After completing the course, I am now much more confident in working on numpy arrays and also have quite good understanding of dimensions. Recommended for Data Scientist and ML Engineers.

L
Lakshya8 July 2021

There were literally 100+ exercises on numpy and that too of such a good level. Very good course to have.

A
Adison5 July 2021

1. The subtitle is too small to read on iPad landscape mode. 2. Too many mute section in clips during speaker typing code, this is not a nature experience. Some while noise or anything is better than mute.


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3286770

Udemy ID

7/1/2020

Course created date

7/6/2020

Course Indexed date
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