AI-900 MS Azure AI Fundamentals

This course is part of Microsoft Azure: Cloud Solutions Mastery Specialization

Instructor: EDUCBA

2,144 already enrolled

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3 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

6 hours to complete

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

6 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Explain core AI concepts, common AI workloads, and Microsoft's responsible AI principles within the Azure ecosystem.
Analyze machine learning models, datasets, and evaluation metrics to understand AI solution performance.
Apply Azure AutoML and ML Designer to build and deploy no-code machine learning models.
Implement AI solutions using Azure Computer Vision, Text Analytics, and Azure Bot Services for intelligent applications.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

11 assignments

Taught in English

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This course is part of the Microsoft Azure: Cloud Solutions Mastery Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
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There are 3 modules in this course

Build a strong foundation in artificial intelligence with Microsoft Azure while preparing for the AI-900 certification. This course introduces core AI concepts, machine learning fundamentals, responsible AI principles, and Azure AI services through practical examples and guided service walkthroughs. You will explore common AI workloads, including computer vision, natural language processing (NLP), and conversational AI, while learning how Azure supports the development of intelligent solutions.

Designed for beginners, business users, and technical decision-makers, this course helps you understand how AI systems work and how to apply Microsoft Azure services to real-world scenarios. You will analyze AI use cases, classify machine learning models, interpret datasets and evaluation metrics, and build no-code machine learning workflows using AutoML and ML Designer. You will also explore Azure Cognitive Services, Text Analytics, Computer Vision, and Azure Bot Services to create intelligent applications, while understanding Microsoft's responsible AI principles for ethical AI implementation. Whether you are preparing for the AI-900 exam or looking to understand Azure AI capabilities, this course provides a structured, practical introduction to AI concepts and Azure-based intelligent solutions, enabling you to confidently evaluate and implement AI technologies in modern organizations.

This module introduces learners to the fundamental concepts of Artificial Intelligence (AI) and its real-world applications. It explains what AI is, how machine learning models function, and the types of workloads typically handled by AI systems. Additionally, the module outlines the structure and requirements of the AI-900 certification exam and explores Microsoft’s approach to responsible AI. Learners will gain insights into AI’s ethical principles, including fairness, accountability, transparency, and security, setting the stage for informed and responsible use of AI technologies within the Microsoft Azure ecosystem.

What's included

9 videos3 assignments

9 videosTotal 57 minutes

Introduction to Course5 minutes
What is Artificial Intelligence6 minutes
Machine Learning Model10 minutes
AI-900 Exam Requirements6 minutes
Common AI workloads10 minutes
Guiding principles for Responsible AI7 minutes
Privacy and Security5 minutes
Transparence and Accountability6 minutes
MS Official website for AI Principles2 minutes

3 assignmentsTotal 50 minutes

Graded - Foundations of AI and Microsoft’s Ethical Principles30 minutes
Introduction and AI Basics10 minutes
AI Workloads and Responsible AI10 minutes

This module delves into the foundational concepts and practical workflows of machine learning within the Azure ecosystem. Learners explore common machine learning types, understand the structure of datasets, and evaluate models using key metrics such as AUC and FPR. The module further introduces Azure’s no-code tools such as AutoML and ML Designer, guiding learners through the complete lifecycle of model creation—from data registration to deployment—without requiring programming expertise. Through visual and automated experiences, learners will develop a solid grasp of how to build, train, and deploy models efficiently in Azure Machine Learning.

What's included

9 videos4 assignments

9 videosTotal 67 minutes

Common ML Types7 minutes
Dataset Features and Labels4 minutes
Training and Validation Dataset8 minutes
FPR and AUC7 minutes
Auto ML6 minutes
Demo-Create Azure ML Workspace7 minutes
Use AutoML to Build a no-Code Model7 minutes
ML Designer5 minutes
ML Designer to Build a no-Code Model15 minutes

4 assignmentsTotal 60 minutes

Graded - Machine Learning Fundamentals and No-Code Tools30 minutes
Understanding Machine Learning Concepts10 minutes
Automated ML and Designer Tools10 minutes
Azure ML Designer10 minutes

This module explores how Microsoft Azure supports a wide range of AI services focused on perception and interaction. Learners will gain foundational knowledge of computer vision, natural language processing (NLP), and conversational AI workloads. They will examine practical applications, explore relevant Azure services, and understand how to build solutions using tools like Computer Vision, Text Analytics, and Azure Bot Services—enabling intelligent interactions through visual recognition, text comprehension, and conversational interfaces.

What's included

9 videos4 assignments

9 videosTotal 47 minutes

Common types of Computer Vision Workloads5 minutes
Computer Vision Services in Microsoft Azure8 minutes
Using Computer Vision Service6 minutes
Using Custom Vision Service7 minutes
NLP Workloads7 minutes
NLP Services5 minutes
Common Types of Conversational AI workloads5 minutes
Conversational AI Services in Azure3 minutes
Conclusion1 minute

4 assignmentsTotal 60 minutes

Graded - Cognitive Services and Conversational AI30 minutes
Computer Vision Workloads on Azure10 minutes
Conversational AI Services10 minutes
Conversational AI Workloads on Azure10 minutes

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Instructor

EDUCBA

1,708 Courses353,508 learners

Offered by

EDUCBA

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