Architect with Azure
Master enterprise Azure architecture and AI services for experienced engineers. Deep dive into Azure OpenAI, Azure ML, cloud-native architectures, security, and advanced Azure design patterns.
4.7
(580 students)
90 hours
What is this course about?
Designed for experienced engineers (3-25 years) looking to become Azure Solutions Architects, Principal Engineers, or Cloud AI Architects. This comprehensive program covers advanced Azure services, Azure OpenAI, and enterprise-scale design that sets senior engineers apart.
What You'll Master:
Advanced Azure Architecture & AI:
• Azure OpenAI Service - GPT-4, GPT-4 Turbo, DALL-E 3, embeddings, function calling, production deployments
• Azure AI Platform - Azure AI Studio, Prompt Flow, AI Search, RAG architectures, model catalog
• Azure Machine Learning - Advanced model training, MLOps pipelines, managed endpoints, custom models
• Compute & Containers - Advanced VM architectures, AKS production patterns, Container Instances, Azure Functions
• Networking at Scale - VNet advanced architectures, Private Link, ExpressRoute, Traffic Manager, Front Door
Enterprise-Grade Azure Skills:
• Azure Cognitive Services: Vision, Speech, Document Intelligence, Language, Translator
• Serverless & Modern Apps: Functions, Logic Apps, Event Grid, Durable Functions orchestration
• Data Platform: Cosmos DB vector search, Azure SQL, Synapse Analytics, Data Factory pipelines
• Infrastructure as Code: ARM templates, Bicep, Terraform on Azure, Azure DevOps pipelines
• Security & Compliance: Azure AD/Entra ID, Key Vault, Managed Identities, Security Center, Sentinel
• Observability: Azure Monitor, Application Insights, Log Analytics, distributed tracing
• Cost Optimization: Azure Cost Management, Reserved Instances, Spot VMs, rightsizing strategies
• Responsible AI: Content Safety, AI governance, bias detection, model explainability
Why Deepskilling for Experienced Engineers:
🚀 Career Acceleration: Transition to Azure Solutions Architect, Principal AI Engineer, Cloud Architect, or AI Platform Lead roles. Master the Azure+AI combination that's transforming enterprises.
💼 Leadership & Impact: Learn to architect Azure AI transformation initiatives, design enterprise GenAI solutions, and lead technical teams. Prepare for Staff+ and principal engineering positions in Azure and AI.
🎯 Advanced Career Support:
• GitHub Portfolio: Build enterprise-grade Azure AI solutions showcasing RAG systems, Azure OpenAI integrations, MLOps pipelines, and production-ready architectures
• LinkedIn Optimization: Position yourself as a Senior/Principal Azure Architect or AI Solutions Architect
• Thought Leadership: Publish advanced Azure AI architecture patterns, GenAI best practices, and enterprise case studies
• Network Expansion: Connect with Azure architects, AI leaders, and hiring managers at Microsoft and enterprise companies
🏆 What Sets This Apart:
✓ Enterprise-scale Azure AI architectures (Fortune 500 GenAI implementations)
✓ Real-world case studies from Microsoft, OpenAI partnerships, enterprise AI deployments
✓ Senior Azure Architects and AI Engineers from Microsoft and top tech companies as mentors
✓ Hands-on labs with Azure OpenAI, RAG systems, and production AI workflows
✓ Capstone: Design and implement a complete Azure AI-powered enterprise solution
✓ Architecture review sessions following Microsoft's Well-Architected Framework
✓ Preparation for Azure Solutions Architect Expert and AI Engineer certifications
✓ Career coaching for senior IC and AI leadership transitions
Perfect for experienced engineers (3-25 years) advancing to Azure Solutions Architect, Principal AI Engineer, Cloud Architect, or AI Platform Engineering leadership roles.
Course Features
Post Graduate Diploma
90 Hours of Content
Hands-on Projects
Community Support
Lifetime Access
Download Course Program
Student Reviews
Vikram Singh
Incredible AI/ML program! Learning to deploy models across AWS SageMaker, Azure ML, and Vertex AI gave me a huge competitive advantage. Landed a Generative AI role at ₹8 LPA!
Cognizant Technology SolutionsDivya Krishnan
The perfect blend of AI theory and hands-on cloud deployment. Building real chatbots and computer vision apps across multiple clouds made my portfolio stand out. Highly recommended!
Capgemini IndiaSarah Chen
As someone new to AI, this course made complex ML concepts accessible. The multi-cloud approach is brilliant—employers love that I can work with any platform. Amazing job assistance too!
NVIDIA SingaporeAditya Rao
The generative AI modules are cutting-edge! Learning Azure OpenAI, AWS Bedrock, and Vertex AI positioned me perfectly for the AI boom. Got hired as Junior AI Developer within a month.
Deloitte ConsultingMeera Joshi
Best AI engineering program for beginners! The structured approach from fundamentals to deployment, plus career coaching, helped me transition from student to AI engineer seamlessly.
Wipro TechnologiesDaniel Park
Outstanding curriculum covering all major cloud AI services. The hands-on projects with real datasets and the MLOps modules prepared me for production AI work. Excellent value!
Amazon Web ServicesRohan Verma
From ML novice to deployment-ready in 24 weeks! The interview prep for AI roles and the portfolio building guidance were invaluable. Now working on enterprise AI solutions.
Tech MahindraShreya Gupta
The AI engineering mentorship and real-world project experience exceeded expectations. The LinkedIn optimization helped recruiters find me. Got 3 job offers before graduation!
Infosys LimitedNeha Kulkarni
Comprehensive AI training with practical multi-cloud deployment skills. The capstone project—a complete AI application—became my portfolio centerpiece. Highly recommend for graduates!
HCL TechnologiesLisa Martinez
The depth of AI/ML coverage plus career support is exceptional. Learning to integrate AI services across all three major clouds makes you incredibly valuable to employers. Love it!
Google Cloud AI