# AI Learning Community Exploration Assignment
# Introduction: Learning Communities & Mini-Projects
In this course, you will work in learning communities focused on different areas of Azure AI services. These communities will help you:
- Explore AI tools available in Azure.
- Learn from peers working on similar AI applications.
- Develop a small project using out-of-the-box AI services.
- Present your work, explain how the service functions, and demo your application.
# How It Works
- Choose a broad AI application area that interests you (e.g., Computer Vision, NLP, Generative AI, etc.).
- In class, find others interested in the same area and form small groups (ideally 3 people).
- As a group, explore AI services within your area and identify a service you want to use.
- Build a mini-project using that service and integrate it into an application.
- Present your project, discuss how the service works, and take questions.
In this first assignment you will explore potential applications of AI that interest you. By the end of this assignment, you will:
✅ Have an Azure account set up.
✅ Have chosen an AI application area to explore further.
✅ Be ready to form a team and start exploring specific services within that area.
# Step 1: Set Up Azure for Students
- Sign up for Azure for Students (instructions will be provided).
- Explore the Azure AI Foundry to see available services.
- Review the AZ-900 learning path to understand key AI applications in Azure.
- Take notes on the AI areas that interest you.
# Step 2: Explore AI Application Areas
Choose an AI application area that interests you. Here are the available options:
# Computer Vision
- AI for image recognition, object detection, and document processing.
- Examples: OCR (extracting text from images), face recognition, object classification.
# Natural Language Processing (NLP)
- AI for understanding and processing text or speech.
- Examples: Sentiment analysis, chatbots, automatic translation, speech-to-text.
# Document Intelligence & AI Search
- AI for knowledge mining and structured document processing.
- Examples: Automating data extraction from documents, intelligent search tools.
# Generative AI
- AI that creates new content, such as text, images, or code.
- Examples: Using Azure OpenAI’s GPT models for text generation, AI-generated images.
# Step 3: Discussion Post
Write a short discussion post (around 150-250 words) that includes:
- The AI application area you are interested in (Computer Vision, NLP, Document Intelligence, or Generative AI).
- Why it interests you – What excites you about this area?
- Ideas for what you might build – What kind of project could you imagine creating with AI in this area? It doesn’t have to be final—just a few ideas.
Post your response in the discussion forum before class.
# Step 4: In-Class Group Formation
- During class, you will find your learning community based on shared AI interests.
- Within the community, form teams of 2-3 around a specific service.
- Begin discussing which AI service to explore further and potential project ideas.