Introduction

This course provides a foundational understanding of Microsoft Azure AI services, designed to help you build your skills in AI solutions and apply them to real-world business scenarios. As Azure continues to be a leading cloud platform, its AI services offer robust tools for machine learning, cognitive services, and AI-powered automation. In this training, you will explore the core components of Azure AI, including an introduction to machine learning, natural language processing, computer vision, and conversational AI, all within the context of Microsoft Azure. By the end of the course, you will be equipped with the fundamental knowledge to start leveraging Azure AI tools and services.

Prerequisites

• Basic understanding of cloud computing concepts
• Familiarity with general AI concepts
• Basic knowledge of Microsoft Azure
• Experience with general programming concepts (helpful but not required)
• Willingness to learn about machine learning and AI techniques

Table of Contents

1. Introduction to Microsoft Azure AI
   1.1 Overview of Microsoft Azure and AI Services
   1.2 Key Benefits of Azure AI
   1.3 Exploring Azure AI Solutions for Businesses
   1.4 Introduction to Azure AI Tools and Resources
2. Getting Started with Azure Machine Learning
   2.1 What is Azure Machine Learning?
   2.2 Setting Up Your Azure Machine Learning Workspace
   2.3 Working with Azure Machine Learning Studio
   2.4 Deploying and Managing ML Models in Azure
3. Cognitive Services Overview
   3.1 What are Azure Cognitive Services?
   3.2 Categories of Cognitive Services
   3.3 Using Pre-built AI Models for Vision, Speech, and Text
   3.4 Integrating Cognitive Services into Applications
4. Azure AI and Natural Language Processing (NLP)
   4.1 Introduction to Natural Language Processing
   4.2 Text Analytics with Azure Cognitive Services
   4.3 Language Understanding (LUIS) for Intent Recognition
   4.4 Sentiment Analysis and Text Translation with Azure AI
5. Computer Vision with Azure AI
   5.1 Introduction to Computer Vision
   5.2 Using Azure Computer Vision API
   5.3 Object Detection and Image Classification
   5.4 Optical Character Recognition (OCR) with Azure AI
6. Conversational AI with Azure Bot Services
   6.1 What is Conversational AI?
   6.2 Building and Deploying Intelligent Bots with Azure Bot Services
   6.3 Integrating Bots into Messaging Platforms
   6.4 Managing Conversations and Dialogs with Azure Bot Framework
7. Azure AI and Data Science
   7.1 Introduction to Data Science with Azure AI
   7.2 Working with Azure Databricks(Ref: Mastering Amazon Redshift: Advanced Database Training)
   7.3 Building and Training Models in Azure Machine Learning
   7.4 Using Azure AI for Data-Driven Decision Making
8. AI Model Deployment and Management in Azure
   8.1 Deploying AI Models in Azure
   8.2 Scaling and Managing AI Models
   8.3 Continuous Monitoring and Performance Tuning of Models
   8.4 Automating AI Workflows with Azure AI
9. Ethics and Responsible AI with Azure
   9.1 Understanding Responsible AI Principles
   9.2 Addressing Bias and Fairness in AI Models
   9.3 Ensuring Transparency and Accountability in AI Applications
   9.4 Best Practices for Building Ethical AI Solutions
10. Real-World Use Cases and Applications of Azure AI
    10.1 Case Study: AI-Powered Customer Service Solutions
    10.2 Case Study: AI in Healthcare and Diagnostics
    10.3 Case Study: Intelligent Automation in Finance
    10.4 Future Trends in AI and Microsoft Azure

Conclusion

Upon completion of this foundational course, you will have acquired the essential skills needed to navigate Microsoft Azure’s AI offerings. You will understand the core components of Azure’s machine learning and cognitive services, and how they can be used to develop, deploy, and manage AI-driven applications. This knowledge will help you build a strong foundation for working with AI technologies and set you on the path toward further specialization in Azure AI.

Reference