May 1, 2024
4 minute read
On-premises computing, also known as on-premise or on-prem, is a computing model in which an organization hosts its own IT infrastructure, typically in a data center located on the organization's premises. This means that the organization owns and manages all of the hardware, software, and other components required to operate its IT systems, as opposed to using cloud computing services from a third-party provider.
What is On-Premises Computing?
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Find a path to becoming a On-Premises Computing. Learn more at:
OpenCourser.com/topic/in43a2/on
Reading list
We've selected 11 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
On-Premises Computing.
Provides a hands-on guide to machine learning with Apache Spark, a popular open-source framework for distributed data processing. It covers topics such as data preparation, feature engineering, model training, and evaluation.
Provides a comprehensive guide to GCP Security, a cloud security platform from Google. It covers topics such as security monitoring, threat detection, and incident response.
Provides a hands-on guide to cloud computing with Microsoft Azure, a popular public cloud platform. It covers topics such as cloud architecture, cloud security, and cloud DevOps.
Provides a comprehensive guide to Azure Security Center, a cloud security platform from Microsoft. It covers topics such as security monitoring, threat detection, and incident response.
Provides a step-by-step guide to building a private cloud, including planning, design, implementation, and management. It also covers best practices and case studies.
Provides a comprehensive guide to Apache Hadoop, a popular open-source framework for distributed data processing. It covers topics such as data storage, processing, and analysis.
Provides a comprehensive guide to deep learning with Python, a popular programming language for machine learning. It covers topics such as neural networks, image processing, and natural language processing.
Provides a comprehensive overview of reinforcement learning, a type of machine learning that allows agents to learn by interacting with their environment. It covers topics such as Markov decision processes, value functions, and reinforcement learning algorithms.
Provides a deep dive into the design of data-intensive applications, including the use of on-premises and cloud infrastructure. It covers topics such as data storage, processing, and analysis.
Provides a comprehensive overview of cloud computing, including on-premises, public, and hybrid models. It also covers the benefits and challenges of cloud computing and provides guidance on planning, implementing, and managing cloud projects.
Provides a comprehensive overview of cloud computing, including on-premises, public, and hybrid models. It also covers the benefits and challenges of cloud computing and provides guidance on planning, implementing, and managing cloud projects.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/in43a2/on
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