AI-900: Microsoft Azure AI Fundamentals

AI-900 introduces the core concepts of Artificial Intelligence and Microsoft Azure services, helping you build foundational knowledge in AI and machine learning.

AI-900: Microsoft Azure AI Fundamentals Certification & Training

Emigo Networks offers comprehensive training for AI-900: Microsoft Azure AI Fundamentals, designed to introduce learners to the core concepts of artificial intelligence and machine learning. This course covers essential AI workloads and services available on Microsoft Azure, helping participants understand how to build and implement AI solutions. Ideal for beginners, the training provides practical insights into Azure AI tools, enabling learners to confidently explore AI technologies and kickstart their journey in the rapidly evolving AI landscape.

Course Overview

The AI-900: Microsoft Azure AI Fundamentals certification is designed for individuals seeking to demonstrate foundational knowledge of artificial intelligence (AI) concepts and Microsoft Azure services. This course covers essential topics such as AI workloads, machine learning principles, computer vision, natural language processing, and conversational AI. It is ideal for those new to AI or Azure, providing a solid base for further role-based certifications like Azure AI Engineer Associate. No prior technical experience is required, making it accessible to both technical and non-technical audiences.

What You'll Learn

Core principles and concepts of Artificial Intelligence (AI) and how they are implemented using Microsoft Azure services
Understanding of machine learning (ML) and how Azure supports ML processes
Basics of computer vision, including image classification, object detection, and facial recognition
Fundamentals of Natural Language Processing (NLP), including text analytics and language understanding
Introduction to conversational AI, including use of Azure Bot Services
Identification of Azure services for AI workloads and how to evaluate responsible AI principles
Insight into considerations for fairness, reliability, privacy, and inclusiveness in AI solutions

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Syllabus Summary

Describe Artificial Intelligence workloads and considerations (15–20%)

a. Identify features of common AI workloads

Identify computer vision workloads
Identify natural language processing workloads
Identify document processing workloads
Identify features of generative AI workloads

b. Identify guiding principles for responsible AI

Describe considerations for fairness in an AI solution
Describe considerations for reliability and safety in an AI solution
Describe considerations for privacy and security in an AI solution
Describe considerations for inclusiveness in an AI solution
Describe considerations for transparency in an AI solution
Describe considerations for accountability in an AI solution

Describe fundamental principles of machine learning on Azure (15-20%)

a. Identify common machine learning techniques

Identify regression machine learning scenarios
Identify classification machine learning scenarios
Identify clustering machine learning scenarios
Identify features of deep learning techniques
Identify features of the Transformer architecture

b. Describe core machine learning concepts

Identify features and labels in a dataset for machine learning
Describe how training and validation datasets are used in machine learning

c. Describe Azure Machine Learning capabilities

Describe capabilities of automated machine learning
Describe data and compute services for data science and machine learning
Describe model management and deployment capabilities in Azure Machine Learning

Describe features of computer vision workloads on Azure (15–20%)

a. Identify common types of computer vision solution

Identify features of image classification solutions
Identify features of object detection solutions
Identify features of optical character recognition solutions
Identify features of facial detection and facial analysis solutions

b. Identify Azure tools and services for computer vision tasks

Describe capabilities of the Azure AI Vision service
Describe capabilities of the Azure AI Face detection service

Describe features of Natural Language Processing (NLP) workloads on Azure (15–20%)

a. Identify features of common NLP Workload Scenarios

Identify features and uses for key phrase extraction
Identify features and uses for entity recognition
Identify features and uses for sentiment analysis
Identify features and uses for language modeling
Identify features and uses for speech recognition and synthesis
Identify features and uses for translation

b. Identify Azure tools and services for NLP workloads

Describe capabilities of the Azure AI Language service
Describe capabilities of the Azure AI Speech service

Describe features of generative AI workloads on Azure (20–25%)

a. Identify features of generative AI solutions

Identify features of generative AI models
Identify common scenarios for generative AI
Identify responsible AI considerations for generative AI

b. Identify generative AI services and capabilities in Microsoft Azure

Describe features and capabilities of Azure AI Foundry
Describe features and capabilities of Azure OpenAI service
Describe features and capabilities of Azure AI Foundry model catalog

Pre-requisites

A basic understanding of cloud computing concepts
Familiarity with Microsoft Azure services is helpful but not required
An interest in Artificial Intelligence and its practical applications
General knowledge of programming or data concepts (optional but advantageous)

Required Exams

Exam Codes: AI-900: Microsoft Azure AI Fundamentals
Length: 45 minutes
Registration fee: $99 USD (+taxes applicable)

Who Should Attend

Beginners and non-technical professionals interested in learning the fundamentals of AI and its applications using Microsoft Azure
Business stakeholders and decision-makers who want to understand how AI can solve business challenges
Students and recent graduates exploring a career in AI or cloud technologies
Technical professionals looking to validate their foundational knowledge of AI concepts and Azure services
Project managers and product owners working on AI-driven projects who need a baseline understanding of AI capabilities on Azure

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What is the AI-900 certification?

AI-900 is a foundational certification that introduces core concepts of artificial intelligence (AI) and how they are implemented using Microsoft Azure services.

Who should take the AI-900 training?

It is suitable for individuals with both technical and non-technical backgrounds who are interested in understanding AI solutions and Microsoft Azure AI services.

What are the core topics covered in the AI-900 course?

The course includes AI workloads, principles of machine learning, computer vision, natural language processing (NLP), and conversational AI on Azure.

What is the official exam fee for AI-900?

The Microsoft AI-900 certification exam costs approximately USD 99, subject to local taxes and exchange rates.

Does Emigo offer online AI-900 training?

Yes, Emigo provides instructor-led online training, suitable for remote learners and professionals with flexible schedules.

Is onsite training available in Kochi for AI-900?

Yes, classroom-based onsite training is conducted at Emigo's Kochi center for individuals and teams.

Does Emigo offer corporate AI-900 training?

Yes, Emigo delivers customized corporate training programs aligned with organizational AI learning goals and project needs.

Can individuals opt for personal AI-900 certification training?

Yes, Emigo supports personalized training paths tailored for students, working professionals, and career changers.

What is the duration of the AI-900 training course?

The course typically runs for 1 to 2 days, depending on the learning mode and participant requirements.

Are there any prerequisites to join the AI-900 course?

There are no mandatory prerequisites. A basic understanding of cloud concepts and interest in AI technologies is helpful.

How does Emigo ensure practical exposure during training?

The training includes demos and real-world use cases using Azure AI services like Cognitive Services and Azure Machine Learning.

How can I register for AI-900 training at Emigo Networks?

You can enroll by contacting Emigo Networks through their website, phone, or visiting their Kochi training center.

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