Python NumPy: Scientific Computing with Python
Free E - Certificate Included | CPD & IAP Accredited | Access for 365 days | No Hidden Fee
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Summary
- Exam(s) / assessment(s) not included in price, and must be purchased separately
Overview
NumPy refers to an open source library that is used for the Python programming language. It is one of the tools used by Python for scientific computing and data analysis purposes. It is mainly used in matrix computing and is used to perform mathematical and logical operations, fourier transform, shape manipulation, linear algebra and random number generation. It was created by Travis Oliphant in 2005 and currently has many contributors for it. A typical NumPY package includes a powerful N-dimensional array, sophisticated functions and tools for integrating C/C++.
NumPy is an essential tool for other scientific Python packages such as scikit-learn, skiPy and OpenCV. As a programmer, it is crucial to be acquainted with all of the Python computing libraries in order to be smart enough to know when to choose one over the other. This Python NumPy: Scientific Computing with Python course provides a thorough understanding of NumPy’s features and when to use them. This course will walk you through the importance of NumPy and to develop an understanding of the scenarios in which NumPy is most useful. You will also be able to get grips on topics such as matrices, deviations, Eigen values, and covariance through this course. This certificate can be that additional qualification that paves way for you to land a rewarding job in the IT or programming field. Therefore, mastering the features of NumPy will help you in kick starting a career in programming and to improve your existing expertise in programming.
* Free E-certificate (No additional cost for E-certificates)
CPD
Course media
Description
Learning outcomes
- Learn why NumPy should be used.
- Understand how to install NumPy
- Gain an understanding of how to use NumPy.
- Gain an insight into topics such as matrices, deviations, Eigen values, and covariance.
Course Curriculum
1: Introduction
2: What Is Numpy
3: Basic Mathematics
4: Tour Of Numpy I
5: Tour Of Numpy Ii
6: Matrices
7: Deviations
8: Eigen Values
9: Covariance
10: Project (Determinants)
11: Summary
Access duration
The course will be directly delivered to you, and you have 12 months access to the online learning platform from the date you joined the course. The course is self-paced and you can complete it in stages, revisiting the lectures at any time.
Method of assessment
At the end of the course, you will have one assignment to be submitted (you need a mark of 65% to pass) and you can submit the assignment at any time. You will only need to pay £19 for assessment and certification when you submit the assignment. You will receive the results within 72 hours of submittal, and will be sent a certificate in 7-14 days if you have successfully passed.
Certification and awarding body
Those who successfully complete the course will be awarded the Python NumPy: Scientific computing with Python certificate by CPD & iAP. The qualification will make you valuable to employers, and your motivation at gaining new skills will be recognised.
Who is this course for?
- IT students
- Job seekers
- IT professionals
Requirements
This course requires no formal prerequisites and this certification is open to everyone
Career path
- Programmer analyst – £31,275 per annum
- Senior programmer analyst – £42,098 per annum
- Software engineer- £34,671 per annum
- Software tester – £30,661 per annum
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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.
