Python NumPy Full Course (2024)

Learn NumPy with 70+ hands-on live running coding examples and exercises

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Python NumPy Full Course (2024)

What You Will Learn!

  • Learn NumPy for Data Science (2024)
  • Learn NumPy from scratch
  • Acquire essential NumPy skills for numeric and scientific computing
  • Be able to program in NumPy professionally.
  • Practice your skills with 70+ exercises
  • Learn NumPy best practices

Description

Welcome to The Complete NumPy Tutorial by Studyopedia.

NumPy is an open-source Python library, that allows you to work with multi-dimensional arrays and matrices, with the mathematical functions operating on these arrays. It stands for Numerical Python and is written in Python and C. It is a Python library for numeric and scientific computing. It consists of multi-dimensional array objects. It is faster with less LOC.

Python NumPy is considered one of the most powerful and top libraries for Data Science. In this course, we have covered over 70 examples to explain every concept of NumPy.

Numpy allows you to perform various operations on Arrays, including

  • Array Slicing

  • Array Join

  • Array Split

  • Array Reshape

  • Array Indexing

  • Array Search

Course Lessons

  1. NumPy Introduction

  2. Installing NumPy with pip

  3. Create NumPy arrays

  4. Dimensions in NumPy Arrays

  5. Initialize NumPy Arrays

  6. Datatypes in NumPy

  7. NumPy Array Indexing

  8. NumPy Array Slicing

  9. NumPy Array Shape

  10. Reshape a NumPy array

  11. Iterate NumPy Arrays

  12. Joining NumPy Arrays

  13. Split NumPy Array

  14. Search an Array for a value

  15. Sorting NumPy Arrays

  16. Axes in NumPy arrays

  17. Intersection of NumPy Arrays

  18. Difference between NumPy arrays

  19. Arithmetic Operations on NumPy arrays

  20. Scalar operations on NumPy arrays

  21. Statistical Operations on NumPy arrays

  22. Random module in NumPy

  23. NumPy Logs

  24. NumPy LCM and HCF


Quiz

We have also provided 6 Online Quizzes to polish your NumPy skills after completing the lessons.

100+ live coding examples are covered to make each lesson easier for the students.

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Who Should Attend!

  • Get started with NumPy
  • Those who want to learn NumPy by doing. This course includes 50+ hands-on exercises
  • Gain a deep understanding of Python NumPy
  • Python Libraries Beginners

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Subscribers

168

Lectures

24

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