
Define artificial intelligence, its capabilities, and the ethical principles of responsible AI. Explore six AI workloads and the four pillars—predict, decide, converse, see—plus azure Foundry integration.
Explore AI agents through a browser-based model, learning how local hardware affects inferencing, model choices, and how chatbots like ChatGPT operate as stateless, generative AI.
Explore how gen AI models convert text into tokens and embeddings, then apply attention in a transformer to predict the next word. See how tokens, embeddings, and attention drive generation.
Explore how AI agents differ from standalone models, and why grounding sources steer responses in structured output. Learn choosing small language models for devices with limited connectivity in Azure.
Contrast statistical text analysis with semantic models, tracing NLP from word counting to embedding-based meaning spaces that fuel large language models and transformer-era approaches.
Compare general purpose AI models with Azure language for text analytics, highlighting deterministic structured outputs, confidence scores, and capabilities like language detection, named entity recognition, and PII redaction.
Compare CNNs and vision transformers, noting CNNs' local feature extraction and vision transformers' global context via patch embeddings and attention, plus diffusion and multimodal models.
Explore content understanding in the foundry portal with predefined analyzers like OCR and form extraction. Learn to deploy models and handle asynchronous JSON outputs with confidence scores.
The AI-901 certification is Microsoft's newest validation of practical AI knowledge — and in 2026, it is becoming a baseline expectation for cloud professionals, developers, and anyone building with Azure. This course prepares you to pass it with confidence while giving you the real-world AI foundation that goes far beyond the exam itself.
This is a complete, structured course covering every objective in the AI-901 exam — from core AI and machine learning concepts to Azure AI services for computer vision, natural language processing, speech, and generative AI — alongside responsible AI principles and practical implementation patterns used across industries today.
Built by Sandeep Soni, a corporate trainer with over 30 years of technology training experience and 20+ Microsoft certifications, this course reflects the teaching approach that has helped more than 500,000 IT professionals across the USA, UK, Australia, and the Middle East build practical, job-ready technical skills.
Every lesson is designed around real-world implementation, architectural understanding, and hands-on demonstrations rather than slide-based theory. Sandeep's philosophy is simple: decision training, not tool training. Instead of merely showing features and commands, he focuses on helping students understand why technologies work the way they do, how they fit into real engineering workflows, and how to make informed technical decisions in production environments.
What makes this course different?
Most AI-901 prep courses are either too brief to build real understanding or too theoretical to be useful after the exam. This course takes a different approach — every concept is explained clearly, grounded in real Azure service examples, and structured so that what you learn for the exam is directly applicable in a professional Azure environment. You will not just memorize definitions. You will understand how AI actually works in Azure and why it matters.
The course is fully updated for the 2026 exam objectives, covering the Microsoft Foundry ecosystem, large language models, and generative AI capabilities that are now a core part of the AI-901 syllabus and were absent from earlier AI-900 preparation materials.
What you will master, topic by topic:
AI and Machine Learning Fundamentals — Build a solid conceptual foundation in artificial intelligence and machine learning before touching any Azure service. You will understand the difference between training and inference, how ML models learn from data, and the key workload types that appear consistently across the exam and in real projects.
Azure AI Services — Explore the full range of Azure AI capabilities: computer vision for image analysis and object detection, natural language processing for text analytics and language understanding, and speech services for audio-to-text and text-to-audio workflows. You will understand what each service does, when to use it, and how it maps to real business scenarios.
Generative AI and Large Language Models — Understand how large language models work, what Azure OpenAI Service provides, and how generative AI capabilities are integrated into modern Azure applications. This is among the most heavily tested areas of the current AI-901 exam and is covered in full depth here.
Responsible AI Principles — Microsoft's Responsible AI framework is an exam requirement and a professional standard. You will learn all six principles — fairness, reliability, privacy, inclusiveness, transparency, and accountability — and how they apply to the design and deployment of AI systems in Azure.
Certification Readiness — Every section is mapped directly to the AI-901 exam objectives. By the end of the course, you will know which concepts to expect, how questions are typically framed, and how to approach the exam with confidence.
Your transformation:
By completing this course, you will hold a clear, working understanding of how artificial intelligence is implemented across the Azure platform — not as an abstract concept, but as a set of real services with real capabilities. You will be ready to sit the AI-901 exam and to contribute meaningfully to AI-enabled projects in any cloud or technology role.
Whether you are a developer, cloud professional, IT administrator, or business professional working alongside technical teams, the knowledge you build here will give you a credible foundation in one of the most in-demand skill areas in enterprise technology today.
Enroll now and take the first step toward your AI-901 certification.