AI-900: Microsoft Azure AI Fundamentals
Be thoroughly prepared for the exam and immediately learn how to apply AI services and concepts in Azure in practice.
AI is no longer futuristic; it’s a daily reality in modern software. From chatbots and speech recognition to intelligent search and image analysis, Microsoft Azure offers countless ways to easily integrate AI. The AI-900 certification helps you understand how this technology works and how to apply it responsibly. You’ll learn the core principles of AI, machine learning, and Azure AI services and how to translate them into practical use within your organization.
Learn to apply AI responsibly and effectively
This certification track helps you build insight into the key AI concepts and building blocks within the Azure ecosystem. After completion:
- You understand the basics of AI and machine learning, including training and validation processes
- You can distinguish between AI models, their goals, and use cases
- You know which Azure services support language, vision, speech, and decision-making
- You can evaluate AI solutions in terms of reliability, privacy, and ethics
- You’re fully prepared for the Microsoft AI-900 exam
What you’ll learn
The content is based on the official Microsoft exam guide and offers a broad introduction to AI with Azure:
- Core AI principles
- AI use cases: classification, prediction, detection, automation
- Differences between AI, machine learning, deep learning, and generative AI
- Understanding datasets, training and validation processes
- Working with Azure Machine Learning
- Setting up workspaces in Azure Machine Learning Studio
- Training and publishing simple ML models
- AutoML and responsible AI usage
- Using Azure AI services
- Azure Cognitive Services:
- Language Services (translation, sentiment analysis, text analysis)
- Vision Services (image recognition, facial detection, OCR)
- Speech Services (speech-to-text and text-to-speech)
- Decision Services (anomaly detection, personalization)
- Azure OpenAI Service: Introduction to generative AI and large language models
- Azure AI Search and RAG concepts
- Azure Cognitive Services:
- Responsible AI usage
- Principles of Responsible AI
- Privacy, fairness, accountability, and transparency
- Governance and compliance in AI projects
Practical info
- Target audience: Software and data engineers, consultants, and IT professionals who want foundational knowledge of AI concepts and Azure services
- Level: Fundamentals (entry level)
- Duration: Tailored, depending on knowledge level and needs
- Location: Remote or classroom-based
- Materials: Official Microsoft course material, supplemented with practical cases
- Cost: Depends on training needs and program duration
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