====== 30 Day Plan to Deploy AI in Azure ====== Here's a **30-day learning and preparation plan** to get ready to **deploy and support Azure AI solutions**, assuming you're working **full-time (5 days/week, 8 hours/day)**. This plan is focused on practical skills, foundational knowledge, and hands-on experience across **Azure AI services** like Azure OpenAI, Azure Machine Learning, Cognitive Services, and Bot Services. ---- **๐Ÿง  Week 1: Azure Fundamentals & AI Overview** **Goal:** Build foundational Azure and AI service knowledge. **Day 1โ€“2: Azure Core Concepts** * Learn: * Azure architecture, subscriptions, resource groups, regions * Azure Portal, CLI, Resource Manager (ARM templates) * Hands-on: * Set up Azure subscription and sandbox * Deploy basic resources (e.g., Storage, VMs) * Resources: * Microsoft Learn: Azure Fundamentals **Day 3โ€“4: Introduction to Azure AI Services** * Learn: * Overview of Azure AI stack: Azure Machine Learning, Azure OpenAI, Cognitive Services, AI Search * Use cases and architecture patterns * Hands-on: * Explore Azure AI Studio * Try out basic pre-built models (e.g., language, vision) * Resources: * Azure AI documentation * Azure AI Fundamentals (AI-900) **Day 5: Basic Governance & Security** * Learn: * Role-Based Access Control (RBAC), managed identities * Azure Key Vault and AI service permissions * Hands-on: * Configure access and secrets for an AI service ---- **โš™๏ธ Week 2: Azure OpenAI & Cognitive Services** **Goal:** Deploy and manage foundational AI APIs and large language models. **Day 6โ€“7: Azure OpenAI Service** * Learn: * Models: GPT, Embeddings, Prompts, Token limits * Responsible AI & content filtering * Hands-on: * Deploy Azure OpenAI resource * Use GPT-4 in a simple chat app or data Q&A * Resources: * Azure OpenAI Service Documentation * Prompt Engineering Guide (e.g., OpenAI Cookbook) **Day 8โ€“9: Azure Cognitive Services** * Learn: * Key APIs: Vision, Speech, Language, Translator * Use case integration (e.g., OCR, sentiment analysis) * Hands-on: * Create and test multiple cognitive service APIs in the Azure Portal and with Python/REST * Resources: * Cognitive Services Overview **Day 10: Monitoring and Cost Management** * Learn: * Azure Monitor, Metrics, Logs * Cost management tools and quotas * Hands-on: * Set up alerts, budget thresholds, and diagnostic logging ---- **๐Ÿงช Week 3: Azure Machine Learning** **Goal:** Deploy ML workflows and models using Azure Machine Learning. **Day 11โ€“12: Azure Machine Learning Basics** * Learn: * Workspaces, compute targets, environments * Notebooks, data assets, model registration * Hands-on: * Build and deploy a basic ML model using AutoML or a notebook * Resources: * Azure ML Fundamentals **Day 13โ€“14: Pipelines and Responsible AI** * Learn: * ML pipelines, scheduling, and versioning * Responsible AI dashboard, model explainability * Hands-on: * Create and run an ML pipeline * Review fairness and explainability metrics **Day 15: Real-World Deployment** * Learn: * Real-time vs batch inference * Endpoint management and scaling * Hands-on: * Deploy and consume a model endpoint from a web app or script ---- **๐Ÿค– Week 4: Bots, Integration, and Final Practice** **Goal:** Prepare for real-world deployment, integration, and troubleshooting. **Day 16โ€“17: Bot Framework & AI Integration** * Learn: * Azure Bot Service, Bot Framework Composer * Integration with LLMs and Cognitive Services * Hands-on: * Build and deploy a chatbot integrated with Azure OpenAI **Day 18โ€“19: Enterprise Readiness & CI/CD** * Learn: * Infrastructure-as-code (Bicep, ARM, Terraform) * GitHub Actions / Azure DevOps for model deployment * Hands-on: * Build a simple CI/CD pipeline for an ML model or bot **Day 20: Review & Mock Deployment** * Task: * Design and deploy a full-stack demo AI solution (e.g., document Q&A bot, image analyzer) * Include monitoring, secure endpoints, and user access ---- **๐Ÿ“˜ Bonus: Certification & Continuing Education** * **Optional**: Prepare for **AI-102** (Designing and Implementing Azure AI Solutions) if you're aiming to validate your skills. * Ongoing learning via: * Microsoft Learn * GitHub examples and the OpenAI Cookbook * Azure AI YouTube channels and blogs **๐Ÿ—‚๏ธ Trello Board Structure: "Azure AI 30-Day Learning Plan"** **๐Ÿงญ List: Week 1 โ€“ Azure & AI Fundamentals** **Cards:** * โœ… Set up Azure subscription and sandbox environment * ๐Ÿง  Learn Azure core services (VMs, Storage, Networking, ARM) * ๐Ÿ› ๏ธ Practice deploying resources via Portal and CLI * ๐Ÿ” Learn Azure AI services: OpenAI, Cognitive Services, Azure ML * ๐Ÿงช Test prebuilt models in Azure AI Studio * ๐Ÿ” Learn RBAC, Managed Identities, and Azure Key Vault * ๐Ÿ”ง Set up Key Vault secrets for AI services ---- **๐Ÿง  List: Week 2 โ€“ OpenAI & Cognitive Services** **Cards:** * ๐Ÿ“š Learn Azure OpenAI: GPT, models, use cases, limits * โš™๏ธ Deploy Azure OpenAI resource and test with prompt playground * ๐Ÿ’ฌ Build a simple chat demo using OpenAI completion/chat API * ๐Ÿ” Learn Cognitive Services: Language, Vision, Speech, Translator * ๐Ÿงช Build an app using at least 2 Cognitive Service APIs * ๐Ÿ“Š Explore monitoring: Logs, metrics, diagnostics for AI resources * ๐Ÿ’ต Set up budgets and quotas in Cost Management ---- **โš™๏ธ List: Week 3 โ€“ Azure Machine Learning** **Cards:** * ๐Ÿง  Learn Azure ML: Workspaces, Compute, Notebooks, Environments * โš™๏ธ Create a dataset and run an AutoML training job * ๐Ÿงช Train and register a model manually via notebook * ๐Ÿ” Learn ML pipelines: Build and run a simple pipeline * ๐ŸŒ Deploy a model as a real-time endpoint * ๐Ÿ” Review fairness/explainability using Responsible AI dashboard * ๐Ÿงฉ Test consuming your endpoint from a REST client or app ---- **๐Ÿค– List: Week 4 โ€“ Bots, Integration & End-to-End Deployment** **Cards:** * ๐Ÿค– Learn Azure Bot Service + Bot Framework Composer * ๐Ÿ”ง Build and deploy a bot integrated with OpenAI * ๐Ÿ› ๏ธ Learn Infrastructure-as-Code with Bicep or Terraform * ๐Ÿ” Create a CI/CD pipeline for ML model or bot using GitHub Actions * ๐Ÿ“ˆ Add logging, alerts, and diagnostics to your solution * ๐Ÿงช Perform a mock deployment of a full AI solution (e.g., Q&A bot) * ๐Ÿ”„ Review architecture for scalability and security ---- **๐Ÿ List: Done โœ…** * Move cards here once completed ---- **๐Ÿ“Œ Extra Lists (Optional):** **๐Ÿ“– Resources** * Microsoft Learn: Azure AI * Azure AI Studio: https://ai.azure.com * Azure OpenAI: https://learn.microsoft.com/en-us/azure/ai-services/openai/ * Azure ML Notebooks: https://github.com/Azure/MachineLearningNotebooks **๐Ÿงฉ Certification Prep** * AI-900: Azure AI Fundamentals * AI-102: Designing and Implementing Azure AI Solutions [[wiki:ai:home-page|AI Cloud Managed Services Policies and Procedures]]