Microsoft Azure AI Fundamentals: Computer Vision
Azure AI Vision Essentials: From Pixels to Insights Description
- Build production-ready solutions
- Implement security systems via facial recognition
- Master Azure AI Vision Studio
- Optimize costs
- Prepare for certification
- Address ethical AI
- Align with industry
- Build a base for specialized roles in AI development or cloud engineering
- Prepare for more advanced Microsoft certifications in AI
What you will learn
Microsoft Azure AI Fundamentals: Computer Vision is a beginner-friendly course designed to teach the core principles of AI-driven visual perception using Azure services. Over three modules (1h 46m total), learners explore image analysis, facial recognition, and optical character recognition (OCR) through hands-on Azure AI Vision Studio labs. The curriculum aligns with AI-900 certification objectives, covering practical scenarios like extracting text from invoices, detecting emotions in customer photos, and automating quality control in manufacturing. Key tools include Azure's pre-trained Vision API for object detection and Face API for demographic analysis. No prior coding experience is required, making it ideal for developers, business analysts, and IT professionals seeking to implement AI-powered vision solutions.
Microsoft's Microsoft Azure AI Fundamentals: Computer Vision course Outline
Learn the Microsoft Azure AI Fundamentals: Computer Vision
Want to turn images into actionable insights? Microsoft's Azure AI Computer Vision course teaches you to extract text, analyze faces, and automate workflows—no coding needed. With free Azure labs and AI-900 exam prep, it's perfect for developers and business teams. Start your 1.5-hour journey today and unlock AI's visual superpowers!
Start your journey today:
Course Structure Includes:
Module 1: Computer Vision Basics
- Image processing pipelines: Grayscale conversion, edge detection.
- Hands-on lab: Classify product defects in manufacturing images using Vision Studio.
Module 2: Facial Recognition
- Emotion detection (anger, joy), demographic analysis (age, gender).
- Exercise: Build a customer sentiment tracker for retail stores.
Module 3: OCR & Document Intelligence
- Extract handwritten notes, receipts, and forms using Read API.
- Lab: Convert scanned medical records into structured databases.
Training Options
Self Paced Learning
- Lifelong access to high-quality content
- Curated by industry experts
- Customized learning progress
- 24/7 learner assistance and support
- Follow the latest technology trends
Exam Dump
- 100% Real Exam Practice Tests
- 100% Verified Exam Questions & Answers
- 100% Guarantee Passing Rate
- Average 7 Days to Practice & Pass
Description
Master Azure's computer vision tools: Analyze images, detect faces, and extract text with AI Vision Studio. Prep for AI-900 certification in under 2 hours.
Pre-requisites
Ability to navigate the Azure portal
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Benefits of AWS Certified AI Practitioner Certification
Microsoft Certified: Azure AI Fundamentals (AI-900) is an entry-level certification designed to validate foundational knowledge of AI and machine learning concepts, including computer vision, natural language processing (NLP), generative AI, and responsible AI principles. Ideal for both technical and non-technical professionals, it requires no prior coding experience and offers free, flexible learning resources via Microsoft Learn. The certification enhances career prospects in high-demand roles like AI Engineer or Data Scientist, with potential salary increases up to 20%, while serving as a gateway to advanced Azure certifications (e.g., AI-102). Cost-effective and time-efficient (preparation in 10–30 hours), the exam focuses on real-world applications using Azure Cognitive Services, OpenAI APIs, and Azure Machine Learning. With permanent validity and global recognition across 90+ countries, it equips professionals to drive AI innovation in industries such as healthcare and finance. Start your AI journey with Microsoft Learn today!
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SPOTO's study resources provide comprehensive coverage of the exam syllabus, aligning with key topics like ML problem framing, data processing, model optimization, and pipeline automation. The materials include structured learning paths, practice exams, and real-world case studies that mirror the certification's focus on designing, implementing, and deploying machine learning solutions with Microsoft services and ML workflows. By leveraging SPOTO's targeted content, candidates can efficiently bridge knowledge gaps, reinforce practical skills, and gain familiarity with the exam format. This focused preparation increases confidence and readiness, particularly for complex tasks such as deploying CI/CD pipelines or optimizing model performance—areas emphasized in the certification. Combined with hands-on experience, SPOTO's resources offer a strategic advantage for achieving certification success.
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