30 Days Of Python Code: Numpy Challenge 2023

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Improve your Python & NumPy programming skills and solve over 200 exercises!


  • basic knowledge of Python
  • basic knowledge of NumPy
  • I have courses which can assist in obtaining all the necessary skills for this course


Take the 30 days of code challenge! Welcome to the 30 Days of Python Code: NumPy Challenge course where you can test your Python & NumPy programming skills.

Topics you will find in the basic exercises:

  • arrays creation
  • shapes, reshaping arrays
  • dimensions
  • size
  • indexing
  • slicing
  • arrays manipulation
  • math, statistic & calculations
  • dates
  • random
  • comparing arrays
  • broadcasting
  • saving, loading & exporting
  • appending, concatenating & stacking arrays
  • sorting, searching & counting
  • filtering
  • boolean mask
  • image as an array
  • dealing with missing values
  • iterating over arrays
  • linear algebra
  • matrix multiplication
  • polynomials
  • solving systems of equations
  • arrays with characters
  • functional programming & universal functions
  • dummy encoding
  • and other

This course is designed for people who have basic knowledge of NumPy and Python. It consists of 200 exercises with solutions and 2 practical tests. The first test is after 15 days, the second after 30 days. This is a great test for people who are learning the Python language & NumPy and are looking for new challenges. Exercises are also a good test before the interview.

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

Stack Overflow Developer Survey

According to the Stack Overflow Developer Survey 2021, Python is the most wanted programming language. Python passed SQL to become our third most popular technology. Python is the language developers want to work with most if they aren’t already doing so.

Who this course is for:

  • everyone who wants to learn by doing
  • everyone who wants to improve their Python programming skills
  • everyone who wants to improve their NumPy skills
  • everyone who wants to improve their data science skills
  • everyone who wants to prepare for an interview

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