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Cloudswyft

Microsoft Future Ready: Introduction to Azure Cloud for Data Scientists

Cloudswyft via FutureLearn

Overview

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This two-week course is part of Data Science on Microsoft Azure using R Programming ExpertTrack, where you’ll learn the fundamentals of the research process in data science.

Learn how to improve your data science processes using Microsoft Azure. By using this powerful tool and learning about cloud computing concepts, you can streamline your delivery of business-critical data analysis.

Delve into data science and types of cloud computing

Under the guidance of industry experts at Cloudswyft, you’ll grow your knowledge of the different business models for cloud and AI usage of cloud computing. With an understanding of the right tools for your organisation, you can create a more robust and efficient data science project.

You’ll develop your understanding of general cloud computing concepts and cloud computing models. You’ll also learn about services such as public, private, and hybrid cloud as well as Platform-as-a-Service (PaaS), Software-as-a-Service (SaaS), and Infrastructure-as-a-Service (IaaS).

Using the market-leading tools of Microsoft Azure and Amazon Web Services (AWS), you’ll apply these cloud computing concepts by looking at data science solutions.

Understand data science options in Microsoft Azure

You’ll explore the many products available within Microsoft Azure including Azure Stream Analytics, Azure Data Explorer, and Azure Synapse Analytics.

You’ll gain an understanding of how to use these to support development, data analytics, and database creation.

Unlock the potential of Amazon Web Services (AWS)

Learn how to prepare the infrastructure you need for your projects, reduce your maintenance time and cut costs within your department by developing your understanding of AWS.

You’ll review the features within AWS and how you can use it to suit your data projects.

This course was developed for people who would like to learn data science applications of cloud computing services, particularly Microsoft Azure and Amazon Web Services.

Taught by

Daniela Piedrahita

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