Udemy

Python Data Science with NumPy: Over 100 Exercises

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  • 64,123 Students
  • Updated 4/2025
4.6
(194 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
0 Hour(s) 47 Minute(s)
Language
English
Taught by
Paweł Krakowiak, Tomasz Krakowiak
Rating
4.6
(194 Ratings)
2 views

Course Overview

Python Data Science with NumPy: Over 100 Exercises

Level up Your Data Science Skills in Python - Unleash the Power of Numerical Computing and Analysis!

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 Content

  • 10 section(s)
  • 116 lecture(s)
  • Section 1 Tips
  • Section 2 Starter
  • Section 3 Exercises 1-10
  • Section 4 Exercises 11-20
  • Section 5 Exercises 21-30
  • Section 6 Exercises 31-40
  • Section 7 Exercises 41-50
  • Section 8 Exercises 51-60
  • Section 9 Exercises 61-70
  • Section 10 Exercises 71-80

What You’ll Learn

  • solve over 100 exercises in NumPy
  • deal with real programming problems in data science
  • work with documentation and Stack Overflow
  • guaranteed instructor support

Reviews

  • S
    Shuaiqi Huang
    5.0

    well organized and covered most used functions

  • D
    Daneeshkumar S
    4.0

    good explanation. keep it up

  • G
    Gabriel NICOD
    4.5

    fun and playful way to learn

  • G
    Gayathri Varatharaju
    4.0

    Interest to learn more about python

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