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The Role of the Data ONTAP Storage System within Windows Environments

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In this course that has a time duration of one hour, a certified instructor of NetApp Alicia Townsend covers the job of the Data ONTAP framework of storage inside the environment of Windows.

Self-Paced

Learning Style

NetApp

Provider

Beginner

Difficulty

1 Hour

Course Duration

Course Info

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In this course that has a time duration of one hour, a certified instructor of NetApp Alicia Townsend covers the job of the Data ONTAP framework of storage inside the environment of Windows.

Course Information

About this course:

In this course that has a time duration of one hour, a certified instructor of NetApp Alicia Townsend covers the job of the Data ONTAP framework of storage inside the environment of Windows. Reasonable for individuals who work with the technologies of NetApp and hybrid cloud environments.

Course Objective:

To have a point by point conversation on the job of Data ONTAP storage frameworks in an environment of MS Windows.

Audience:

NetApp Administrators

Individuals who work with hybrid cloud environments and NetApp technologies.

Prerequisite:

Should be aware of the technologies of NetApp.

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More Information
Brand	NetApp
Subjects	IT Ops & Management
Lab Access	No
Technology	NetApp
Learning Style	Self-Paced Learning
Learning Type	Course
Difficulty	Beginner
Course Duration	1 Hour
Language	English

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Tom is an innovator first, and then a Data Scientist & Software Architect. He has integrated expertise in business, product, technology and management. Tom has been involved in creating category defining new products in AI and big data for different industries, which generated more than hundred million revenue cumulatively, and served more than 10 million users.
As a Data Scientist and Software Architect Tom has extensive experience in data science, engineering, architecture and software development. To date Tom has accumulated over a decade of experience in R, Python & Linux Shell programming.

Tom has expertise on Python, SQL, and Spark. He has worked on several libraries including but not limited to Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn, SciPy, NLTK, Keras, and Tensorflow.