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AI-900: Microsoft Certified Azure AI Fundamentals

Introduction

Course Introduction

Welcome to Microsoft Azure AI Fundamentals (AI-900)! I’m Ravindra Skaria, and I’ll be your guide on this journey into the exciting world of artificial intelligence. In today's rapidly evolving AI landscape, it's essential to grasp not only the core capabilities of AI but also the importance of responsible usage. This course is designed to help you transition from foundational theory to practical, real-world applications using Azure's powerful AI services.

You'll begin by understanding what AI is, exploring its common applications, and examining the ethical principles essential for responsible AI implementation.

Machine Learning Fundamentals

In this section, we dive into the fundamentals of machine learning. You will learn about various types of machine learning, including both supervised and unsupervised learning, and see practical examples such as regression, classification, and clustering.

The image is a diagram explaining types of machine learning, including supervised and unsupervised learning, with examples like regression, classification, and clustering. It also features a small inset of a person in the bottom right corner.

You'll also gain hands-on experience with model training, explore deep learning techniques, and discover how Azure Machine Learning simplifies the development and deployment of AI/ML solutions.

Azure AI Services

Next, we introduce the suite of Azure AI tools and services designed to empower you to quickly incorporate intelligence into your applications.

The image is a slide from a presentation titled "Azure Machine Learning – Introduction," showing a diagram of Azure's cloud-based machine learning platform and a screenshot of the Azure Machine Learning Studio interface. A person is also visible in a small circular inset at the bottom right.

In this module, you'll also explore the essentials of Azure AI. This includes critical components such as Subscription, Resource Group, as well as various Azure compute services.

The image is a slide titled "Fundamentals of Azure AI," showing a diagram of cloud components like Subscription, Resource Group, and Resource, alongside Azure compute services such as Virtual Machine, Kubernetes Services, and Functions. There's also a small inset of a person speaking.

Computer Vision with Azure

Step into the world of computer vision, where you'll learn everything from the basics of image processing to advanced techniques using Convolutional Neural Networks. Azure's computer vision capabilities will enable you to analyze and interpret visual data effectively. This module covers a range of features from face detection to optical character recognition (OCR) and includes hands-on experience with Vision Studio for testing and deploying vision-based applications.

Natural Language Processing (NLP)

In the Natural Language Processing (NLP) section, you'll explore techniques for text analytics and conversational AI. Learn how to harness Azure NLP services—including Language Studio and Speech Studio—to build applications that understand and respond to human language. Additionally, this module covers Azure AI Document Intelligence, which provides tools for document analysis and automated data extraction.

The image is a presentation slide about AI Document Intelligence Services, featuring a screenshot of a document analysis interface and a list of features such as structured data representation and analysis options.

Using Azure Document Intelligence, you can extract valuable insights from forms, contracts, and other documents.

Azure AI Search and Generative AI

Learn how Azure AI Search enhances information retrieval through advanced knowledge mining and data enrichment techniques, making it easier to locate and use data efficiently.

Generative AI, a revolutionary breakthrough in technology, is also a key focus of this course. You'll explore how to train language models, integrate Microsoft Copilot services, and leverage Azure Generative AI tools to create and enhance applications with custom prompts and models. Azure OpenAI plays a central role by supporting advanced models and integrating seamlessly with the Azure ecosystem.

Below is a sample Python code snippet illustrating a simple function along with its unit tests. This example demonstrates how to implement and verify basic functionality in your projects:

def add_numbers(a, b):
    return a + b

# Unit tests for the add_numbers function
def test_add_numbers():
    assert add_numbers(3, 4) == 7
    assert add_numbers(0, 10) == 10
    assert add_numbers(4, 0) == 4

def test_add_numbers_negative():
    assert add_numbers(-1, 10) == 9
    assert add_numbers(-10, -1) == -11

Responsible Generative AI

Note

This section underscores the importance of ethical AI practices. Tools like content filters help ensure that your AI solutions are safe, fair, and aligned with industry standards.

The course concludes by focusing on Responsible Generative AI, emphasizing how to plan and deploy ethical AI solutions using Azure's comprehensive resources. To reinforce your learning, mock exams are provided to bolster your confidence as you prepare for the certification exam. These assessments are designed to be beginner-friendly and effective for testing your understanding of the material.

At KodeKloud, community matters. We invite you to join our vibrant forum where you can ask questions, share insights, and support fellow learners. Your participation strengthens our learning ecosystem, making it a great place to interact with peers and experts alike.

Whether you're new to AI or looking to integrate intelligent solutions into your work, the AI-900 course will guide you from foundational concepts to practical applications using Azure’s platform. Join us on this journey to unlock the power of AI with confidence—enroll today and get started!

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