Python Data Science with NumPy: Over 100 Exercises

Python Data Science with NumPy: Over 100 Exercises, available at $69.99, has an average rating of 4.6, with 116 lectures, 103 quizzes, based on 190 reviews, and has 63733 subscribers.

You will learn about solve over 100 exercises in NumPy deal with real programming problems in data science work with documentation and Stack Overflow guaranteed instructor support This course is ideal for individuals who are data analysts or data scientists who want to enhance their skills in data manipulation and numerical computing using the NumPy library in Python or students or individuals with a background in data analysis, statistics, or related fields who want to gain practical experience in using NumPy for data manipulation and analysis or programmers or software developers who are interested in data science and want to learn how to use the NumPy library to efficiently handle large datasets and perform numerical computations or professionals working with scientific or numeric data who want to leverage the power of NumPy to perform advanced calculations, data transformations, and statistical analysis or self-learners who are passionate about data science and want to develop proficiency in using NumPy for data manipulation, analysis, and numerical computations or researchers or scientists in fields such as physics, biology, or engineering who want to apply numerical methods and data analysis techniques using NumPy in Python It is particularly useful for data analysts or data scientists who want to enhance their skills in data manipulation and numerical computing using the NumPy library in Python or students or individuals with a background in data analysis, statistics, or related fields who want to gain practical experience in using NumPy for data manipulation and analysis or programmers or software developers who are interested in data science and want to learn how to use the NumPy library to efficiently handle large datasets and perform numerical computations or professionals working with scientific or numeric data who want to leverage the power of NumPy to perform advanced calculations, data transformations, and statistical analysis or self-learners who are passionate about data science and want to develop proficiency in using NumPy for data manipulation, analysis, and numerical computations or researchers or scientists in fields such as physics, biology, or engineering who want to apply numerical methods and data analysis techniques using NumPy in Python.

Enroll now: Python Data Science with NumPy: Over 100 Exercises

Summary

Title: Python Data Science with NumPy: Over 100 Exercises

Price: $69.99

Average Rating: 4.6

Number of Lectures: 116

Number of Quizzes: 103

Number of Published Lectures: 116

Number of Published Quizzes: 103

Number of Curriculum Items: 219

Number of Published Curriculum Objects: 219

Original Price: $19.99

Quality Status: approved

Status: Live

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

Who Should Attend

data analysts or data scientists who want to enhance their skills in data manipulation and numerical computing using the NumPy library in Python
students or individuals with a background in data analysis, statistics, or related fields who want to gain practical experience in using NumPy for data manipulation and analysis
programmers or software developers who are interested in data science and want to learn how to use the NumPy library to efficiently handle large datasets and perform numerical computations
professionals working with scientific or numeric data who want to leverage the power of NumPy to perform advanced calculations, data transformations, and statistical analysis
self-learners who are passionate about data science and want to develop proficiency in using NumPy for data manipulation, analysis, and numerical computations
researchers or scientists in fields such as physics, biology, or engineering who want to apply numerical methods and data analysis techniques using NumPy in Python

Target Audiences

data analysts or data scientists who want to enhance their skills in data manipulation and numerical computing using the NumPy library in Python
students or individuals with a background in data analysis, statistics, or related fields who want to gain practical experience in using NumPy for data manipulation and analysis
programmers or software developers who are interested in data science and want to learn how to use the NumPy library to efficiently handle large datasets and perform numerical computations
professionals working with scientific or numeric data who want to leverage the power of NumPy to perform advanced calculations, data transformations, and statistical analysis
self-learners who are passionate about data science and want to develop proficiency in using NumPy for data manipulation, analysis, and numerical computations
researchers or scientists in fields such as physics, biology, or engineering who want to apply numerical methods and data analysis techniques using NumPy in Python

The course “Python Data Science with NumPy: Over 100 Exercises” is a practical, exercise-oriented program aimed at individuals who want to strengthen their Python data science skills, with a particular focus on the powerful NumPy library. It caters to learners eager to dive deep into the functionalities that NumPy offers for handling numerical data efficiently.

Each section of the course contains a set of carefully curated exercises designed to consolidate the learners’ understanding of each concept. Participants will get to tackle real-life problems that simulate challenges faced by data scientists in their everyday roles. Each exercise is followed by a detailed solution, helping students understand not just the ‘how’ but also the ‘why’ of each solution.

The “Python Data Science with NumPy: Over 100 Exercises” course is suited for individuals at various stages of their data science journey – from beginners just starting out, to more experienced data scientists looking to refresh their knowledge or gain more practice working with NumPy. The primary prerequisite is a basic understanding of Python programming.

NumPy – Unleash the Power of Numerical Python!

NumPy, short for Numerical Python, is a fundamental library for scientific computing in Python. It provides support for arrays, matrices, and a host of mathematical functions to operate on these data structures. This course is structured into various sections, each targeting a specific feature of the NumPy library, including array creation, indexing, slicing, and manipulation, along with mathematical and statistical functions.

Course Curriculum

Chapter 1: Tips

Lecture 1: A few words from the author

Lecture 2: Configuration

Lecture 3: Tip

Chapter 2: Starter

Lecture 1: Solution 0

Lecture 2: NumPy – Intro

Chapter 3: Exercises 1-10

Lecture 1: Solution 1

Lecture 2: Solution 2

Lecture 3: Solution 3

Lecture 4: Solution 4

Lecture 5: Solution 5

Lecture 6: Solution 6

Lecture 7: Solution 7

Lecture 8: Solution 8

Lecture 9: Solution 9

Lecture 10: Solution 10

Chapter 4: Exercises 11-20

Lecture 1: Solution 11

Lecture 2: Solution 12

Lecture 3: Solution 13

Lecture 4: Solution 14

Lecture 5: Solution 15

Lecture 6: Solution 16

Lecture 7: Solution 17

Lecture 8: Solution 18

Lecture 9: Solution 19

Lecture 10: Solution 20

Chapter 5: Exercises 21-30

Lecture 1: Solution 21

Lecture 2: Solution 22

Lecture 3: Solution 23

Lecture 4: Solution 24

Lecture 5: Solution 25

Lecture 6: Solution 26

Lecture 7: Solution 27

Lecture 8: Solution 28

Lecture 9: Solution 29

Lecture 10: Solution 30

Chapter 6: Exercises 31-40

Lecture 1: Solution 31

Lecture 2: Solution 32

Lecture 3: Solution 33

Lecture 4: Solution 34

Lecture 5: Solution 35

Lecture 6: Solution 36

Lecture 7: Solution 37

Lecture 8: Solution 38

Lecture 9: Solution 39

Lecture 10: Solution 40

Chapter 7: Exercises 41-50

Lecture 1: Solution 41

Lecture 2: Solution 42

Lecture 3: Solution 43

Instructors

Paweł Krakowiak
Python Developer/Data Scientist/Stockbroker

Rating Distribution

1 stars: 4 votes
2 stars: 5 votes
3 stars: 30 votes
4 stars: 53 votes
5 stars: 98 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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