Azure AI Fundamentals (AI-900)

Learning Outcomes

✓ Explain core AI/ML concepts and responsible AI principles

✓ Describe Azure options for building, hosting, and governing AI solutions

✓ Navigate Azure Machine Learning to train, register, and deploy a simple model

✓ Interpret security, identity, and compliance building blocks (RBAC, Defender for Cloud, Purview, STP)

✓ Estimate cost with Azure Pricing/TCO tools and choose data/storage/connectivity options

Curriculum

12-Week Curriculum

Week	Session A	Session B	Micro-lab / Checkpoint
1	Introduction to AI & Azure overview	ML basics on Azure	Identify an AI use-case and map to Azure services
2	Model development with Azure Machine Learning	Experiment tracking & model registry	Train a starter model in Azure ML (UI)
3	AI project management & security basics	Intro to Azure NLP services	Call a text analytics API in a notebook
4	App hosting options on Azure	Azure ExpressRoute (private connectivity)	Compare connectivity patterns for an AI API
5	Storage redundancy (LRS/ZRS/GZRS/GRS)	Data migration options	Choose storage + redundancy for a scenario
6	AI-900 core topic review 1	Azure Directory Services (Entra ID)	Role/identity mapping exercise
7	External Identities (B2B/B2C)	RBAC fundamentals in Azure	Design least-privilege roles for an AI app
8	Defender for Cloud: overview & use	Pricing & TCO calculator	Calculate monthly cost for a sample workload
9	Microsoft Purview overview	Purview governance scope & purpose	Draft a simple data catalog and glossary
10	Service Trust Portal (STP): concepts	Using STP artifacts (compliance reports)	Locate compliance docs for a region
11	Azure Resource Manager (ARM)	ARM templates & IaC basics	Read an ARM/Bicep snippet; identify resources
12	AI-900 mock exam 1	AI-900 mock exam 2 + final review	Mock exam reflection & study plan

The Microsoft Azure AI Fundamentals (AI-900) certification validates foundational knowledge of AI and machine learning concepts on Azure.