Zero Trust is not a product or tool, but an essential security strategy that seeks to continuously verify every transaction, asserts least privilege access, and assumes that every transaction could be a possible attack. Through the modules in this learning path, you'll gain an understanding of Zero Trust and how it applies to identity, endpoints, applications, networks, infrastructure, and data.

Understand the importance of fostering a culture of reliability within organizations to enhance operational performance.

Power BI reports often depend on local data sources. This course will teach how to you use on-premises data gateways to connect the two.

Explore observability principles and practices to enhance monitoring and performance management in cloud environments.

This course will teach you how to effectively lead a successful team by establishing goals, roles, and guidelines that work.

Learn why resource estimation is crucial in the development of quantum computing, and learn how to use the Azure Quantum Resource Estimator.

Despite the clear advantages of public clouds, a great amount of customers are still running workloads on-premises, with cost being of the biggest fear factors. In this course, you'll learn how to confidently define the cost of your Azure resources.

This course will teach you how to do estimation calibration through Structured Expert Judgment to make your forecasts more reliable by calculating and analyzing calibration and information scores.

Master Ethereum development fundamentals. Learn the essentials of the Ethereum ecosystem, from smart contract basics to blockchain integration. Enroll now!

Since Ethernet is a widely used protocol in data networking, you'll spend most of the course examining Ethernet. You'll also examine physical components required for networking, as well as the layer 2 protocols used in network communication.

Master Ethereum dApp and smart contract development with the Ethers.js library. Learn to interact with the Ethereum blockchain through hands-on training.

Explore ethical considerations and frameworks for developing responsible AI systems that align with societal values.