
Learn about key risks and challenges in AI, including privacy, security, bias, and accountability; explore real-world examples like loan approvals, facial recognition, autonomous vehicles, and medical data protection.
Explore how machine learning learns from experience through supervised and unsupervised learning, including classification, regression, and clustering. See examples like spam detection, weather forecasting, and Netflix-style clustering.
Explore evaluating a machine learning model with the best model summary, residuals matrix, and predicted versus actual values, then deploy an endpoint and run notebook predictions.
Build a car price prediction pipeline with data cleaning, missing value handling, and column selection; train a linear regression model on a 70/30 split and evaluate results.
Analyze hotel reviews to demonstrate text analytics workflows, including language detection, key phrase extraction, sentiment analysis, and named entities, using Azure Cognitive Services.
Learn how conversation ai enables chat and voice interfaces across channels, build a knowledge base with q&a, train natural language processing, and ensure transparent virtual assistant behavior with human handoffs.
Build a customer support bot by creating a knowledge base that interprets questions for a website chat, email, and voice interface, with Q&A, Azure deployment, and telemetry.
This course is designed for anyone who wants to learn about artificial intelligence (AI) and ML
This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. The course is not designed to teach students to become professional data scientists or software developers, but rather to build awareness of common AI workloads and the ability to identify Azure services to support them. The course is designed as a blended learning experience that combines instructor-led training with online materials on the Microsoft Learn platform The hands-on exercises in the course are based on Learn modules, and students are encouraged to use the content on Learn as reference materials to reinforce what they learn in the class and to explore topics in more depth.
Microsoft Azure that you can use to build AI solutions. The course provides a practical, hands-on approach in which you will get a chance to see AI in action and try Azure AI services for yourself.
Describe Artificial Intelligence workloads and considerations.
Describe fundamental principles of machine learning on Azure.
Describe features of computer vision workloads on Azure.
Describe features of Natural Language Processing (NLP) workloads on Azure.
Describe features of conversational AI workloads on Azure.
Audience Profile
The Azure AI Fundamentals course is designed for anyone interested in learning about the types of solution artificial intelligence (AI) makes possible, and the services on Microsoft Azure that you can use to create them. You don’t need to have any experience of using Microsoft Azure before taking this course, but a basic level of familiarity with computer technology and the Internet is assumed. Some of the concepts covered in the course require a basic understanding of mathematics, such as the ability to interpret charts. The course includes hands-on activities that involve working with data and running code, so a knowledge of fundamental programming principles will be helpful.