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Azure Cloud Fundamentals for Data Science with Python

Cloudswyft via FutureLearn



Improve and streamline your data science processes using Microsoft Azure. Growing your understanding of cloud computing concepts and tools can help with the delivery of business-critical data analysis.

Understand the data science applications of cloud computing

Finding and adopting the right tools within your organisation is key to robust and efficient data science projects. Guided by industry experts, you’ll grow your understanding of the different business models for cloud and AI usage of cloud computing.

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

You’ll then apply those cloud computing concepts by looking at data science solutions that you can find in Microsoft Azure and Amazon Cloud Services - two market leaders.

Get to grips with the data science options in Microsoft Azure

Microsoft Azure is home to a suite of products that support data analytics, development, and database creation. You’ll explore the opportunities within the platform, such as Azure Stream Analytics, Azure Synapse Analytics, and Azure Data Explorer.

Discover the possibilities within Amazon Web Services (AWS)

A strong understanding of how AWS works will help you to prepare the infrastructure you need for your projects, reduce spend within your department, and spend less time on maintenance. This course will review AWS and how you can use it to best effect for 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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