AI-900T00: Microsoft Azure AI Fundamentals Course Overview

The Microsoft Azure AI Fundamentals (AI 900T00) course is a one-day instructor-led training event designed to help you understand and explore the basics of Artificial Intelligence (AI). The course teaches core concepts related to AI, such as machine learning, deep learning, computer vision, natural language processing (NLP) and more. This course introduces Azure AI services and tools to develop, implement and manage AI solutions in the Azure cloud. Topics such as Data Science, Cognitive Services, Bot Services, Machine Learning, and Metrics/Insights will be discussed, highlighting how to bring AI solutions to life within the Azure platform. At the end of the day, you will have some hands-on experience creating an AI project with Azure.

Course Prerequisites

There are no official prerequisites for the AI-900T00: Microsoft Azure AI Fundamentals Training course. However, it is beneficial to have a basic understanding of cloud computing and Microsoft Azure services in order to get the most out of the course. Additionally, some knowledge of Artificial Intelligence (AI) concepts, such as machine learning and data science, is beneficial.

Target Audience

The AI-900T00 Microsoft Azure AI Fundamentals training is designed for individuals from a wide range of backgrounds
This includes engineers, architects, developers, administrators, data scientists and stakeholders work with or are looking to work with Azure AI services
It is also beneficial to those with data and analytics backgrounds who want to upskill their knowledge on applying advanced analytics with AI in Azure
Though not limited to just those areas, this course will also be beneficial to marketers, decision makers, project and program managers, or anyone looking to get a better understanding of working with the Azure Machine Learning and Cognitive Services product suite

Learning Objectives of AI-900T00: Microsoft Azure AI Fundamentals

1. Understand the purpose and fundamentals of Artificial Intelligence (AI) and Machine Learning (ML), including use cases and current applications.
2. Learn about the features and benefits of Microsoft Azure Cognitive Services and how to use them to create AI solutions.
3. Examine ethical and responsible AI practices, such as data governance, data privacy, and transparency.
4. Create interactive experiences with Azure Bot Services to enable end-users to interact with AI solutions.
5. Explore AI development tools including Azure Machine Learning Studio and Azure Machine Learning Service.
6. Identify solutions for Machine Learning tasks such as Text Analysis, Image Processing, Anomaly Detection, and Forecasting.
7. Learn how to create and deploy machine learning models using Azure ML and MLOps.
8. Discuss the need for integrating AI applications into the enterprise.