Azure Cloud Fundamentals for Data Science with Python
Grow your understanding of key cloud computing concepts and learn how they apply to data science projects in this self-paced course.
Duration
2 weeks
Weekly study
6 hours
100% online
How it works
Included in an ExpertTrack
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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.
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.
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.
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.
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