Use Azure Bot Service to create custom bots that provide enhanced user experiences and augment applications. Examine bot functionality and design. Explore Azure Bot Service tools, including Bot Framework Composer, and when to use them.

Assess the characteristics of Azure Functions for IoT. Describe the function of triggers and bindings and show how you combine them to create a scalable IoT solution. Describe the benefits of using cloud infrastructure to rapidly deploy IoT applications with Azure Functions.

Explain the essential characteristics of the IoT Edge and the functionality of the IoT Edge components (modules, runtime, and cloud interface). Characterize the types of problems that you can solve with IoT Edge. Describe how the elements of IoT Edge can be combined to solve the problem of deploying IoT applications in the cloud.

Assess the characteristics of Azure IoT Hub and determine scenarios when to use IoT Hub.

Determine the types of business problems that can be solved using Azure Sphere. Explain the capabilities and the components (microcontroller unit, operating system, cloud-based security service) for the Azure Sphere. Describe how the components provide a secure platform to develop, deploy, and maintain secure internet connected IoT solutions.

Characterize the types of connectivity options available to the Azure Sphere in an Industrial IoT scenario. Describe the functionality of each of the connectivity options and show how they can be combined to solve complex industrial IoT problems.

Get to know the concept of copilots in the ever evolving generative AI domain. Define how startups can use Azure Copilot Stack and apply best practices to deliver value to their customers.

Learn the fundamentals of electrical circuits, including components, design, and analysis.

Learn Coding with ChatGPT

Get introduced to computer vision concepts and techniques for processing and analyzing visual data.

Gain foundational knowledge of computer vision techniques and applications for processing images and videos.

The power of machine learning models comes from the data that is used to train them. Through content and exercises, we explore how to understand your data, how to encode it so that the computer can interpret it properly, how to clean any errors, and tips that will help you create high performance models.