AI 900 - Azure AI Fundamentals - Introduction

Step 01 - Introduction to Artificial Intelligence & Machine Learning

Step 03 - Exploring Machine Learning vs Traditional Programming

Step 04 - Machine Learning Fundamentals - Scenarios

Step 02 - Exploring Machine Learning Examples

Step 01 - Exploring Pre Trained Models - Cognitive Services

Step 02 - Exploring Vision Related APIs

Step 03 - Exploring Vision - Some Terminology

Step 04 - Getting started with Computer Vision API

Creating Azure Account

Step 05 - Demo - Creating Cognitive Services Multi Service Account

Step 07 - Understanding Computer Vision API - OCR Operations

Step 09 - Exploring Form Recognizer API

Step 10 - Cognitive Services - Vision - Scenarios

Step 06 - Demo - Playing with Computer Vision API

Step 08 - Getting Started with Face API

Step 11 - Getting Started - Cognitive Services - Natural Language Processing

Step 13 - Exploring Translator and Speech API

Step 15 - Demo - Playing with QnA Maker - 1 - Getting Started

Step 14 - Getting Started with Conversational AI

Step 12 - Exploring Text Analytics API

Step 16 - Demo - Playing with QnA Maker - 2 - Setting up Knowledge Base

Step 17 - Demo - Playing with Azure Bot Service

Step 19 - Cognitive Services - NLP - Scenarios

Step 18 - Exploring LUIS Language Understanding Intelligent Service

Step 20 - Understanding Decision Services Make smarter decisions

Step 22 - Cognitive Services - A Quick Review

Step 21 - Cognitive Services - Decision Services and Others

Step 02 - Building ML Models - Custom Vision - 2

Step 03 - Creating ML Models - Features and Labels

Step 01 - Building ML Models - Custom Vision - 1

Step 04 - Creating ML Models - Choosing Technique

Step 06 - Creating Machine Learning Models - Steps

Step 05 - Machine Learning Fundamentals - Scenarios

Step 08 - ML Stages and Terminology - Scenarios

Step 07 - Understanding Machine Learning Terminology

Step 09 - Getting Started with Azure Machine Learning

Step 11 - Demo - Setting up Automated ML Training

Step 12 - Demo - Exploring Automated ML Training

Step 10 - Demo - Automated Machine Learning - Dataset and Compute

Step 13 - Demo - Creating Azure Machine Learning Pipeline

Step 15 - Model Evaluation - Classification Models

Step 16 - ML Model Evaluation - Scenarios

Step 14 - Demo - Model Evaluation - Regression Models

Step 18 - Building Custom ML Models in Azure - Scenarios

Step 01 - Most important AI considerations - Responsible AI Principles

Step 02 - AI considerations - Scenarios

AI 900 - Azure AI Fundamentals - Get Ready

AI 900 - Azure AI Fundamentals - Congratulations