AI-900: Microsoft Azure AI Fundamentals in a Weekend
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I’m here to help you pass the AI-900 Azure AI Fundamentals certification exam!
Do you think learning Artificial Intelligence and Machine Learning is DIFFICULT? What if I can prove you WRONG?
Learn AI and ML Fundamentals in a WEEKEND!
Take your FIRST STEPS into the amazing world of Artificial Intelligence and Machine Learning using a HANDS-ON step by step approach.
BEGINNERS to cloud, Azure, AI and ML are WELCOME!
WHAT LEARNERS ARE SAYING
5 STARS – The course is amazing, just direct to the point
5 STARS – Good course to quickly clear the certification exam.
5 STARS – Another superb course from In28Minutes!
5 STARS – Right to the point and provided short notes were amazing.
6 Things YOU need to know about this AI–900 Course
#1: HANDS-ON – The best way to learn Azure AI Fundamentals is to get your hands dirty!
#2: Designed for ABSOLUTE BEGINNERS to Azure
#3: MULTI-CLOUD INSTRUCTOR – MORE THAN 100,000 Learners are learning AWS, Azure, and Google Cloud with us
#4: COMPLETE PREP for Azure Certification – AI-900 – Microsoft Azure AI Fundamentals
#5: FREE Downloadable PDF – Quickly Review for the exam
#6: FREE Practice Test – Test if you are ready for the exam
Artificial Intelligence (AI) will revolutionize how we do things in the next decade. Cloud is making AI easy! This course is a wonderful introduction to the world of Cloud and Artificial Intelligence. AI-900 Azure AI Fundamentals validates foundational knowledge of machine learning and artificial intelligence concepts and related Microsoft Azure services.
AI-900 Azure AI Fundamentals helps you demonstrate knowledge of:
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AI workloads and considerations
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Fundamental principles of machine learning on Azure
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Features of computer vision workloads on Azure
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Features of Natural Language Processing (NLP) workloads on Azure
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Features of conversational AI workloads on Azure.
Skills measured in AI-900 Azure AI Fundamentals
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Describe AI workloads and considerations
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Describe fundamental principles of machine learning on Azure
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Describe features of computer vision workloads on Azure
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Describe features of Natural Language Processing (NLP) workloads on Azure
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Describe features of conversational AI workloads on Azure
Are you ready to get started on the amazing journey to achieve Azure Certification – AI-900 – Microsoft Azure AI Fundamentals?
Do you want to join 750,000+ learners having Amazing Learning Experiences with in28Minutes?
Look No Further!
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Step 01 - Exploring Pre Trained Models - Cognitive Services -
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Step 02 - Exploring Vision Related APIs
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Step 03 - Exploring Vision - Some Terminology
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Step 04 - Getting started with Computer Vision API
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Creating Azure Account
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Step 05 - Demo - Creating Cognitive Services Multi Service Account
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Step 06 - Demo - Playing with Computer Vision API
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Do you want to help us? -
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Step 07 - Understanding Computer Vision API - OCR Operations
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Step 08 - Getting Started with Face API
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Step 09 - Exploring Form Recognizer API
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Step 10 - Cognitive Services - Vision - Scenarios
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Step 11 - Getting Started - Cognitive Services - Natural Language Processing
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Step 12 - Exploring Text Analytics API
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Step 13 - Exploring Translator and Speech API
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Step 14 - Getting Started with Conversational AI
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Step 15 - Demo - Playing with QnA Maker - 1 - Getting Started
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Step 16 - Demo - Playing with QnA Maker - 2 - Setting up Knowledge Base
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Step 17 - Demo - Playing with Azure Bot Service
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Step 18 - Exploring LUIS/ Language Understanding Intelligent Service
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Step 19 - Cognitive Services - NLP - Scenarios
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Step 20 - Understanding Decision Services/ Make smarter decisions
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Step 21 - Cognitive Services - Decision Services and Others
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Step 22 - Cognitive Services - A Quick Review
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Section Quiz
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Course Downloads - Custom Vision - Images
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Step 01 - Building ML Models - Custom Vision - 1
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Step 02 - Building ML Models - Custom Vision - 2
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Step 03 - Creating ML Models - Features and Labels
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Step 04 - Creating ML Models - Choosing Technique
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Step 05 - Machine Learning Fundamentals - Scenarios
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Step 06 - Creating Machine Learning Models - Steps
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Step 07 - Understanding Machine Learning Terminology
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Step 08 - ML Stages and Terminology - Scenarios
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Do you want to help us?
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Step 09 - Getting Started with Azure Machine Learning
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Step 10 - Demo - Automated Machine Learning - Dataset and Compute
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Step 11 - Demo - Setting up Automated ML Training
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Step 12 - Demo - Exploring Automated ML Training
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Step 13 - Demo - Creating Azure Machine Learning Pipeline
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Step 14 - Demo - Model Evaluation - Regression Models
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Step 15 - Model Evaluation - Classification Models
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Step 16 - ML Model Evaluation - Scenarios
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Step 17 - Azure Machine Learning - Terminology
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Step 18 - Building Custom ML Models in Azure - Scenarios
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Section Quiz
