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AWS Machine Learning


EduCBA

Summary

Price
£149 inc VAT
Or £49.67/mo. for 3 months...
Study method
Online
Duration
Self-paced
Qualification
No formal qualification

Overview

Machine learning is a scientific discipline that explores the construction and study of algorithms that can learn from data. Such algorithms operate by building a model from example inputs and using that to make predictions or decisions, rather than following strictly static program instructions. Machine learning is closely related to and often overlaps with computational statistics; a discipline that also specializes in prediction-making.

Description

Through this training we are going to guide you through the process of building a machine learning model using Amazon Web Services.

The training will include the following;

1. What is Amazon Machine Learning (AML)?

2. Accessing AML

3. Pricing Info

4. ML Concepts

5. Data Formats for ML

6. Using Amazon S3 with AML

7. AML process

8. Evaluating and Interpreting

Target Customers:

  • Anyone who wants to learn about data and analytics
  • Data Engineers
  • Analysts
  • Architects
  • Software Engineers
  • IT operations
  • Technical managers

Pre-Requisites:

  • Prior knowledge of machine learning required
  • Basic knowledge of AWS

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FAQs

Interest free credit agreements provided by Zopa Bank Limited trading as DivideBuy are not regulated by the Financial Conduct Authority and do not fall under the jurisdiction of the Financial Ombudsman Service. Zopa Bank Limited trading as DivideBuy is authorised by the Prudential Regulation Authority and regulated by the Financial Conduct Authority and the Prudential Regulation Authority, and entered on the Financial Services Register (800542). Zopa Bank Limited (10627575) is incorporated in England & Wales and has its registered office at: 1st Floor, Cottons Centre, Tooley Street, London, SE1 2QG. VAT Number 281765280. DivideBuy's trading address is First Floor, Brunswick Court, Brunswick Street, Newcastle-under-Lyme, ST5 1HH. © Zopa Bank Limited 2024. All rights reserved.