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The Complete Python NumPy Tutorial for Data Science (2024)

Learn NumPy with 100+ hands-on live running coding examples and exercises

Amit Diwan

Summary

Price
£12 inc VAT
Study method
Online, On Demand What's this?
Duration
3.4 hours · Self-paced
Qualification
No formal qualification
Certificates
  • Certificate of Completion - Free
  • Reed Courses Certificate of Completion - Free

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Overview

Welcome to The Complete PythonNumPy Tutorial (2024)!!

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

What you'll 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 50+ exercises
  • Learn NumPy best practices

Certificates

Certificate of Completion

Digital certificate - Included

Reed Courses Certificate of Completion

Digital certificate - Included

Will be downloadable when all lectures have been completed.

Curriculum

7
sections
31
lectures
3h 27m
total

Course media

Description

NumPy 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.

Numpy allows you to perform various operations on Arrays, including

  • Array Slicing
  • Array Join
  • Array Split
  • Array Reshape
  • Array Intersection
  • Array Arithmetic Operations
  • Array Statistical Operations

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

We have also provided an Online Quiz 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 is this course for?

  • 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

Requirements

  • A computer with an Internet
  • Python knowledge
  • Passion to learn NumPy

Career path

The Average Data Scientist's salary in the UK is £73,411
The Average Data Analyst salary in the UK is £41,449

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Legal information

This course is advertised on reed.co.uk by the Course Provider, whose terms and conditions apply. Purchases are made directly from the Course Provider, and as such, content and materials are supplied by the Course Provider directly. Reed is acting as agent and not reseller in relation to this course. Reed's only responsibility is to facilitate your payment for the course. It is your responsibility to review and agree to the Course Provider's terms and conditions and satisfy yourself as to the suitability of the course you intend to purchase. Reed will not have any responsibility for the content of the course and/or associated materials.

FAQs

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An endorsed course is a skills based course which has been checked over and approved by an independent awarding body. Endorsed courses are not regulated so do not result in a qualification - however, the student can usually purchase a certificate showing the awarding body's logo if they wish. Certain awarding bodies - such as Quality Licence Scheme and TQUK - have developed endorsement schemes as a way to help students select the best skills based courses for them.
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