Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
7 Hour(s) 36 Minute(s)
Language
English
Taught by
Alan Rodrigues
Rating
Course Overview
AI-900 Microsoft Azure AI Fundamentals Preparation Course
Release v4.0 - August2025
Artificial Intelligence is no longer the future—it’s the present, reshaping how industries operate and how we work, live, and interact. With tools like ChatGPT and Azure AI becoming part of everyday workflows, staying current with AI fundamentals is not just useful—it’s essential.
The entire course has been updated and refreshed. All chapters have been re-recorded. This has been done to ensure that all contents now reflect the most recent changes to the services on the Azure platform.
All course contents have also been aligned as per any changes to the course objectives.
Release v3.0 - January 2025
The entire course has been updated and refreshed. All chapters have been re-recorded. This has been done to ensure that all contents now reflect the most recent changes to the services on the Azure platform.
All course contents have also been aligned as per any changes to the course objectives.
Additional questions also added to the Practice Tests available at the end of the course.
Release v2.0 - July 2023
The entire course has been updated and refreshed. All chapters have been re-recorded. This has been done to ensure that all contents now reflect the most recent changes to the services on the Azure platform.
All course contents have also been aligned as per any changes to the course objectives.
Quiz questions have also been added to the end of each section.
This course is a preparation course for students who want to attempt the Exam AI-900: Microsoft Azure AI Fundamentals
This course has contents for the Exam AI-900
The objectives covered in this course are
Describe AI workloads and considerations (15-20%) - Here we will discuss the the basics on AI-based workloads.
Describe fundamental principles of machine learning on Azure (30-35%) - Here we will understand what is Machine Learning. We will also look at labs on how to work with the Machine Learning service.
Describe features of computer vision workloads on Azure (15-20%) - Here we will look at the different features of the Computer Vision service. We will also look at the Custom Vision service, the Face service and the Form Recognizer service.
Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%) - Here we will look at services such the Text Analytics service, the Language Understanding Intelligence Service , the Speech service.
Describe features of conversational AI workloads on Azure (15-20%) - Here we will see the basics on the QnA Maker service and the Bot Framework.
There is also a number of labs available in this course. These labs focus on the different services available in Azure when it comes to Machine Learning and Artificial Intelligence.
Course Content
- 7 section(s)
- 110 lecture(s)
- Section 1 Introduction and basics on Azure
- Section 2 Describe AI workloads and considerations
- Section 3 Describe fundamental principles of machine learning on Azure
- Section 4 Describe features of computer vision workloads on Azure
- Section 5 Describe features of Natural Language Processing and Conversational AI workloads
- Section 6 Describe features of generative AI workloads on Azure
- Section 7 Practice Section
What You’ll Learn
- This course is designed for individuals who want to demonstrate foundational knowledge of Artificial Intelligence (AI) and its applications in Microsoft Azure.
- Students will learn core concepts of AI, like machine learning, deep learning, natural language processing (NLP), computer vision, and AI solutions in general.
- Students will be learning Fundamental concepts for Artificial Intelligence and Machine Learning
- You will learn the importance of fairness, transparency, accountability, and privacy when designing AI models and solutions.
- Students will learn the workflow of training machine learning models, including data preparation, model building, training, and evaluation.
Skills covered in this course
Reviews
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NNaveen N
I'm glad to inform that the concepts are very interesting to adopt the skills.,
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AAman Mandape
Good course, very thorough on the content. Covers not only theoretical but practical aspects too. Thanks...
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RRashmiranjan Pandey
Very nice to beginner and intermediate level.
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AAnshuman Shukla
In terms of hands-on Lab, it is very good and very detailed. But while explaining a topic, consistency is missing (jumping between multiple things). For Eg: while you are explaining about deployment of pipeline, then you created 1 AKS cluster, but then we used VM to deploy pipeline, then you created a new pipeline and deployed it on AKS cluster. Because of this, it becomes very confusing to understand few basic things, like, if we can deploy pipelines (real time input) on to a VM, or we will always need an AKS cluster for such deployments.
