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Python NumPy: Scientific Computing with Python


Stone River eLearning

Summary

Price
£12 inc VAT
Study method
Online
Duration
1 hour · Self-paced
Qualification
No formal qualification

Overview

At the end of this course, you will have a thorough understanding of Numpy' s features and when to use them. Numpy is mainly used in matrix computing. We'll do a number of examples specific to matrix computing, which will allow you to see the various scenarios in which Numpy is helpful. There are a few computational computing libraries available for Python. It's important to know when to choose one over the other. Through rigorous exercises, you'll experience where Numpy is powerful and develop and understanding of the scenarios in which Numpy is most useful.

  • Express fully why Numpy should be used
  • Ability to install Numpy
  • Understanding of how to use Numpy

What Will I Learn?

  • Express fully why Numpy should be used
  • Ability to install Numpy
  • Understanding of how to use Numpy

Description

Class Curriculum

NumPy

Start

Introduction (1:13)

Preview

What is Numpy (3:12)

Start

Basic Mathematics (6:23)

Start

Tour of Numpy I (8:02)

Start

Tour of Numpy II (10:17)

Start

Matrices (6:56)

Preview

Deviations (3:18)

Start

Eigen Values (5:18)

Start

Covariance (9:55)

Start

Project (Determinants) (9:33)

Start

Summary (1:03)

Who is this course for?

  • Those wanting to know about Python libraries helpful for computational computing

Requirements

  • Some Python experience
  • Some experience working with matrices will be helpful

Career path

Web developer

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FAQs

Study method describes the format in which the course will be delivered. At Reed Courses, courses are delivered in a number of ways, including online courses, where the course content can be accessed online remotely, and classroom courses, where courses are delivered in person at a classroom venue.

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