100+ Exercises - Python Programming - Data Science - NumPy



 


Description

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RECOMMENDED LEARNING PATH

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PYTHON DEVELOPER:

  • 200+ Exercises - Programming in Python - from A to Z

·         210+ Exercises - Python Standard Libraries - from A to Z

·         150+ Exercises - Object Oriented Programming in Python - OOP

·         150+ Exercises - Data Structures in Python - Hands-On

·         100+ Exercises - Advanced Python Programming

·         100+ Exercises - Unit tests in Python - unittest framework

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

·         100+ Exercises - Python Programming - Data Science - Pandas

·         100+ Exercises - Python - Data Science - scikit-learn

·         250+ Exercises - Data Science Bootcamp in Python

 

SQL DEVELOPER:

  • SQL Bootcamp - Hands-On Exercises - SQLite - Part I

·         SQL Bootcamp - Hands-On Exercises - SQLite - Part II

 

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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.

 


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