100+ Exercises – Python – Data Science – NumPy – 2023

COURSE AUTHOR –
Paweł Krakowiak, takeITeasy Academy

Last Updated on April 9, 2023 by GeeksGod

100+ Exercises – Python Programming – Data Science – NumPy

Welcome to the 100+ Exercises – Python Programming – Data Science – NumPy course, 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 arraysgenerating numpy arraysgenerating numpy arrays with random valuesiterating through arraysdealing with missing valuesworking with matricesreading/writing filesjoining arraysreshaping arrayscomputing basic array statisticssorting arraysfiltering arraysimage as an arraylinear algebramatrix multiplicationdeterminant of the matrixeigenvalues and eignevectorsinverse matrixshuffling arraysworking with polynomialsworking with datesworking with strings in arraysolving systems of equations

This 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.

Stack Overflow Developer Survey

According to the Stack Overflow Developer Survey 2021, Python is the most wanted programming language with NumPy being the second most used tool in the “Other Frameworks and Libraries” category. 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.

Udemy Coupon :

E6001DB07327A6D8874B

What you will learn :

1. solve over 100 exercises in NumPy
2. deal with real programming problems in data science
3. work with documentation and Stack Overflow
4. guaranteed instructor support

100% off Coupon

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