The document outlines a comprehensive roadmap for beginners aiming to achieve Azure AI and Azure Cloud Architect certifications, covering essential topics such as cloud computing models, Azure core services, and AI fundamentals. It includes key areas of focus for various segments, recommended resources, and strategies for hands-on experience and exam preparation. The roadmap emphasizes the four steps of learning skills, building experience, empowering oneself with practical applications, and preparing for job interviews.

1. Azure AI & Azure
Cloud Architect
Certification
Swipe
ROADMAP FOR
BEGINNERS
Level Up Your Career
2024 EDITION

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This is crucial for understanding Azure's core services, which are
applicable across AI and cloud architecture roles. You will cover
the basics of cloud computing, Azure fundamentals, and common
tools, which will set a strong foundation for advanced learning.
Key Areas of Focus:
Azure Basics: Learn about cloud computing models (IaaS,
PaaS, SaaS), Azure regions, resource management, and
subscription models.
Azure Portal & CLI: Gain hands-on experience using Azure
Portal and CLI, which are primary interfaces for managing
Azure resources.
Azure Core Services: Familiarize yourself with key services
like virtual machines, Azure Storage, Azure SQL, and Azure
App Service.
Recommended Resources:
Microsoft Learn – Azure Fundamentals Path
Certification: Microsoft Azure Fundamentals (AZ-900)
AZURE AI CERTIFICATION & AZURE CLOUD ARCHITECT ROADMAP
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1 Foundation in Azure
Cloud Services

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With a foundation in Azure, this shifts focus toward AI and
machine learning fundamentals. These skills are vital for the AI
certification and support building intelligent solutions on Azure.
Key Areas of Focus:
AI and Machine Learning Basics: Understand core AI
concepts, types of machine learning (supervised,
unsupervised, reinforcement), and deep learning basics.
Data Processing & Management: Explore Azure Data
Factory, Azure Synapse Analytics, and Azure Blob Storage
for efficient data handling.
Machine Learning Models: Develop skills in model
selection, training, and evaluation using Azure Machine
Learning services.
Recommended Resources:
Microsoft Learn – Azure AI Engineer Path
Certification: Azure AI Engineer Associate (AI-102)
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2 Core AI and Machine
Learning Concepts

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This is the deep dive into Azure AI services and learning to build
real-world AI applications. The focus will be on Cognitive
Services, custom vision, language processing, and AI-driven
solution design.
Key Areas of Focus:
Azure Cognitive Services: Work with APIs for vision,
language, speech, and decision-making models, such as
Azure Bot Service and Translator.
Custom Vision & Natural Language Processing (NLP):
Create custom models using Azure Cognitive Services to
process images and text.
AI Solution Design Patterns: Learn best practices for
architecting scalable and secure AI solutions on Azure.
Recommended Resources:
Microsoft Learn – Advanced AI and Machine Learning
Courses
Certification: Azure AI Engineer Associate (AI-102)
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3 Azure AI Solutions and
Cognitive Services

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This focuses mastering core infrastructure and networking
concepts required for the Azure Solutions Architect certification.
This will help you design, configure, and deploy cloud solutions
efficiently.
Key Areas of Focus:
Virtual Networks & VPNs: Understand how to configure
Azure VNet, VPNs, and ExpressRoute for secure networking.
Load Balancing & Traffic Management: Explore Azure
Load Balancer, Application Gateway, and Traffic Manager to
ensure high availability.
Security & Identity Management: Learn about Azure Active
Directory (AD), role-based access control (RBAC), and
network security.
Recommended Resources:
Microsoft Learn – Azure Solutions Architect Path
Certification: Microsoft Certified: Azure Solutions Architect
Expert (AZ-305)
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4 Azure Infrastructure &
Networking for Architects

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As a certified Azure Solutions Architect, you’ll need to design
reliable, scalable, and cost-effective solutions. This segment
emphasizes data management, storage solutions, and
application design on Azure.
Key Areas of Focus:
Storage Solutions: Work with Azure Blob Storage, Azure
SQL Database, and Cosmos DB for data storage and
management.
Designing Resilient Architectures: Implement strategies
for disaster recovery, high availability, and fault tolerance.
Cost Optimization & Performance Management: Learn
cost-saving techniques, including reserved instances, Azure
Cost Management, and monitoring performance with Azure
Monitor.
Recommended Resources:
Case Studies and Practical Labs for Azure Architect
Certification: Azure Solutions Architect Expert (AZ-305)
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5 Designing Cloud Solutions
and Data Management

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You’ll apply your skills to integrate AI models into enterprise-level
applications and ensure these solutions meet organizational
needs. This will also prepare you for real-world problem-solving
as a certified Azure AI and Cloud Architect.
Key Areas of Focus:
MLOps & DevOps for AI Models: Explore MLOps
frameworks, continuous integration/continuous deployment
(CI/CD) for AI, and model deployment on Azure.
Integration with Azure Kubernetes Services (AKS):
Deploy scalable AI solutions using AKS for model
management and inference.
End-to-End AI Solution Architecture: Architect solutions
that incorporate AI models with Azure services for optimal
performance and scalability.
Recommended Resources:
Advanced Azure AI and Machine Learning Workshops
Certification: Practice Exam and Lab Sessions for Final
Review
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6 Advanced AI and Cloud
Solution Integration

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This final segment is dedicated to intensive preparation for
certification exams and applying knowledge through hands-on
projects. Aim to solve real-life case studies and design end-to-
end solutions for mastery.
Key Areas of Focus:
Practice Exams & Mock Assessments: Take practice
exams for both Azure AI Engineer and Solutions Architect
certifications.
Real-World Project Execution: Work on capstone projects
or case studies in areas like predictive analytics, AI-driven
applications, and hybrid cloud solutions.
Final Review & Knowledge Gaps: Address any remaining
gaps by reviewing notes, re-watching lectures, or retaking
specific labs on areas of improvement.
Recommended Resources:
Microsoft Learn – Certification Exam Readiness Resources
Online Communities for Peer Support and Practice Questions
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7 Exam Preparation &
Practical Experience

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This final segment is dedicated to intensive preparation for
certification exams and applying knowledge through hands-on
projects. Aim to solve real-life case studies and design end-to-
end solutions for mastery.
Key Areas of Focus:
Practice Exams & Mock Assessments: Take practice
exams for both Azure AI Engineer and Solutions Architect
certifications.
Real-World Project Execution: Work on capstone projects
or case studies in areas like predictive analytics, AI-driven
applications, and hybrid cloud solutions.
Final Review & Knowledge Gaps: Address any remaining
gaps by reviewing notes, re-watching lectures, or retaking
specific labs on areas of improvement.
Recommended Resources:
Microsoft Learn – Certification Exam Readiness Resources
Online Communities for Peer Support and Practice Questions
AZURE AI CERTIFICATION & AZURE CLOUD ARCHITECT ROADMAP
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8 Conclusion and
Certification Pathway

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Step1 - Learn Skills: You can practice Azure AI
Certification & Azure Cloud Architect by tutorials on
Azure AI certifications, or through Videos on YouTube
or Videos based courses. For topic revision and
recalling make short notes. You can also learn Live
from Microsoft MVP at ScholarHat.
Step2 - Build Experience: You can build hands-on
experience by building real world applications like
Social Media Platform, Stock Price Monitoring, Fraud
Detection etc.
Step3 - Empower Yourself: Build your strong profile
by mentioning all the above skills with hands-on
experience on projects. Prepare yourself with
interview Q&A about AZURE to crack your next job
interview.
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How to follow this roadmap?
At ScholarHat, we believe mastering a technology
is a three-step process as mentioned below:
AZURE AI CERTIFICATION & AZURE CLOUD ARCHITECT ROADMAP

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You are just one interview away!
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