230+ Exercises Python for Data Science NumPy + Pandas

230+ Exercises – Python for Data Science – NumPy + Pandas, available at $54.99, has an average rating of 4.15, with 248 lectures, 235 quizzes, based on 49 reviews, and has 27263 subscribers.

You will learn about solve over 230 exercises in NumPy and Pandas 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 scientists or analysts who want to strengthen their Python skills specifically for data manipulation, analysis, and exploration using the NumPy and Pandas libraries or students or individuals pursuing a career in data science or data analysis who want to gain hands-on experience with NumPy and Pandas, two essential libraries for data science in Python or programmers or developers who are new to data science and want to learn how to use NumPy and Pandas for data manipulation and analysis tasks or professionals working with large datasets or data analysis projects who want to leverage the power of NumPy and Pandas for efficient data processing and analysis or Python developers interested in expanding their knowledge of data science and want to learn how to use NumPy and Pandas for data manipulation and analysis tasks or self-learners or enthusiasts who are interested in data science and want to develop their Python skills for data manipulation and analysis using NumPy and Pandas It is particularly useful for data scientists or analysts who want to strengthen their Python skills specifically for data manipulation, analysis, and exploration using the NumPy and Pandas libraries or students or individuals pursuing a career in data science or data analysis who want to gain hands-on experience with NumPy and Pandas, two essential libraries for data science in Python or programmers or developers who are new to data science and want to learn how to use NumPy and Pandas for data manipulation and analysis tasks or professionals working with large datasets or data analysis projects who want to leverage the power of NumPy and Pandas for efficient data processing and analysis or Python developers interested in expanding their knowledge of data science and want to learn how to use NumPy and Pandas for data manipulation and analysis tasks or self-learners or enthusiasts who are interested in data science and want to develop their Python skills for data manipulation and analysis using NumPy and Pandas.

Enroll now: 230+ Exercises – Python for Data Science – NumPy + Pandas

Summary

Title: 230+ Exercises – Python for Data Science – NumPy + Pandas

Price: $54.99

Average Rating: 4.15

Number of Lectures: 248

Number of Quizzes: 235

Number of Published Lectures: 248

Number of Published Quizzes: 235

Number of Curriculum Items: 483

Number of Published Curriculum Objects: 483

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

solve over 230 exercises in NumPy and Pandas

deal with real programming problems in data science

work with documentation and Stack Overflow

guaranteed instructor support

Who Should Attend

data scientists or analysts who want to strengthen their Python skills specifically for data manipulation, analysis, and exploration using the NumPy and Pandas libraries

students or individuals pursuing a career in data science or data analysis who want to gain hands-on experience with NumPy and Pandas, two essential libraries for data science in Python

programmers or developers who are new to data science and want to learn how to use NumPy and Pandas for data manipulation and analysis tasks

professionals working with large datasets or data analysis projects who want to leverage the power of NumPy and Pandas for efficient data processing and analysis

Python developers interested in expanding their knowledge of data science and want to learn how to use NumPy and Pandas for data manipulation and analysis tasks

self-learners or enthusiasts who are interested in data science and want to develop their Python skills for data manipulation and analysis using NumPy and Pandas

Target Audiences

data scientists or analysts who want to strengthen their Python skills specifically for data manipulation, analysis, and exploration using the NumPy and Pandas libraries

students or individuals pursuing a career in data science or data analysis who want to gain hands-on experience with NumPy and Pandas, two essential libraries for data science in Python

programmers or developers who are new to data science and want to learn how to use NumPy and Pandas for data manipulation and analysis tasks

professionals working with large datasets or data analysis projects who want to leverage the power of NumPy and Pandas for efficient data processing and analysis

Python developers interested in expanding their knowledge of data science and want to learn how to use NumPy and Pandas for data manipulation and analysis tasks

self-learners or enthusiasts who are interested in data science and want to develop their Python skills for data manipulation and analysis using NumPy and Pandas

The “230+ Exercises – Python for Data Science – NumPy + Pandas” course is an interactive, hands-on course designed for those who are seeking to gain practical experience in data science tools in Python, specifically the NumPy and Pandas libraries. The course contains over 230 exercises that provide learners with a platform to practice and consolidate their knowledge.

The course begins with NumPy, the fundamental package for scientific computing in Python, covering topics like arrays, matrix operations, statistical operations, and random number generation. Learners will practice the use of NumPy functionality through numerous exercises, gaining the proficiency needed for more complex data science tasks.

The course then transitions to Pandas, a library providing high-performance, easy-to-use data structures, and data analysis tools for Python. Here, learners will practice manipulating, cleaning, and visualizing data with Pandas, reinforcing skills necessary for real-world data science projects.

Each exercise is designed to reinforce key concepts and skills, building a strong foundation in handling numerical data and performing advanced data analysis tasks. At the end of the course, learners will have a deep understanding of these libraries and their applications to data science, enhancing their proficiency and readiness for further study or work in this exciting field.

This course is suitable for beginners in Python who have a basic understanding of programming concepts. However, professionals looking to refresh their skills or transition into a data-oriented role may also find it beneficial.

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.

Pandas – Data Empowered, Insights Unleashed!

Pandas is a powerful open-source library in Python that provides easy-to-use data structures and data analysis tools. It is widely used by data scientists, analysts, and researchers for data manipulation, cleaning, exploration, and analysis tasks. Pandas introduces two primary data structures, namely Series (one-dimensional labeled array) and DataFrame (two-dimensional labeled data table), which allow efficient handling of structured data. With Pandas, you can perform various data operations such as filtering, grouping, sorting, merging, and statistical computations. It also offers seamless integration with other libraries in the Python data ecosystem, making it a versatile tool for data wrangling and analysis.

Course Curriculum

Chapter 1: Tips

Lecture 1: A few words from the author

Lecture 2: Requirements

Lecture 3: Configuration

Chapter 2: – NUMPY –

Lecture 1: Intro

Chapter 3: Starter

Lecture 1: Solution 0

Chapter 4: 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 5: 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 6: 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 7: 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 8: Exercises 41-50

Lecture 1: Solution 41

Lecture 2: Solution 42

Lecture 3: Solution 43

Instructors

Pawe? Krakowiak
Python Developer/Data Scientist/Stockbroker

Rating Distribution

1 stars: 3 votes

2 stars: 0 votes

3 stars: 5 votes

4 stars: 12 votes

5 stars: 29 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!