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  3. Azure Cloud AI Architect ..

Azure Cloud AI Architect — Build, Deploy & Scale Real AI Systems

A Proven Curriculum to get an Azure Cloud AI Architect Job of ₹45 LPA*
100% Instructor-led Live Sessions
Learn from Microsoft MVPs
Build AI Apps & Agents with Azure Cloud
Integrate GenAI/LLMs (GPT, DeepSeek)
4 Live projects shipped to Azure
Become Microsoft Certified: Azure AI Engineer
Practice tests to ace AI-102 + interview prep
Dedicated Technical Support
🔥 EMI Options Available*
4.7/5 Rated by 1100+ Learners
Book a FREE Career Growth Session
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25 Jan 2026, 10 AM
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Earn Globally Recognized Certificates

Microsoft Certified Azure AI Engineer Associate: AI-102

The Azure AI Engineer Associate certification verifies that individuals have the skills to create, manage, and deploy AI solutions using Azure Cognitive Services, Cognitive Search, and Microsoft Bot Framework. Attaining this qualification will help them enjoy proliferated careers in the AI domain.

  • Earn Microsoft Certified: Azure AI Engineer Associate Certificate
  • Get access to practice tests to ace the AI-102 exam
  • Earn course completion certificate from ScholarHat

BOOK A FREE DEMO CLASS

Why Become Azure Cloud AI Architect?

Build a Career as an Azure Cloud AI Architect and Earn ₹45 LPA+

Azure Cloud AI Architects design, secure, and scale intelligent cloud systems using Azure AI, Generative AI, and cloud-native architectures. This role combines deep technical expertise with architectural leadership to drive enterprise-scale AI adoption.

Top 1
Cloud Platform

Azure – Enterprise-Grade AI Cloud

Azure is a preferred cloud for enterprises building secure, compliant, and AI-powered solutions.

Cloud-Scale
AI Systems

Architect AI Systems at Scale

Design scalable AI architectures using Azure OpenAI, AI Search, event-driven and microservices patterns.

Leadership
Role

Architects Drive Technical Decisions

Azure Cloud AI Architects guide teams, define standards, and align AI solutions with business goals.

High
Demand

Strong Demand Across Industries

Banking, healthcare, retail, SaaS, and enterprises actively hire AI-focused cloud architects.

₹45 LPA+
Salary

Premium Architect Compensation

Azure Cloud AI Architects command high salaries due to their impact on system design and scalability.

40%+
Growth

AI Architecture Market Growing Rapidly

Organizations are rapidly adopting GenAI, increasing demand for cloud AI architects globally.

Build Real-World Projects

Hands on, work experience-based learning is what makes Scholarhat different from others. Build real world projects by applying your coding skills live with your mentors in just 15 weeks. You’ll learn how to start a project from scratch by following recommended architecture, practices and deploy to server.
Sales Forecasting & Prediction
Utilize Azure ML to predict sales trends and demand for various products. By analyzing historical data, seasonality, and economic factors, this project helps businesses in retail or manufacturing plan inventory and production more accurately.
Fraud Detection System
Build a fraud detection system using Azure ML and anomaly detection algorithms. By analyzing transaction patterns and user behavior, the system can flag suspicious activities, providing enhanced security for financial institutions.
Document Processing System (Powered by Azure AI)
Build a scalable AI-powered document processing system that extracts and classifies information from documents (e.g., invoices, resumes) using Azure AI services, such as Azure Document Intelligence. This project should integrate AI models for OCR, text extraction, and data classification.
Customer Support Chatbot (Powered by Open AI)
Build a scalable AI-driven Customer Support Chatbot using Azure OpenAI services and .NET Core. This chatbot will handle common customer inquiries, offer support, and provide real-time solutions by integrating GPT models for natural language understanding and response generation.
Register For Career Growth Session

Azure AI, Gen AI or Agentic AI Engineer Certification Course Curriculum

The Azure AI, Gen AI or Agentic Engineer Program is designed to cover essential areas, including mastering Python, Machine Learning, and Azure AI and Generative AI. Participants will gain expertise in implementing workloads and security within the Azure framework, skillfully creating and deploying applications in Azure, and ensuring robust data security. This curriculum provides a comprehensive and hands-on understanding of Azure, preparing you to excel as a proficient Azure AI, Gen AI and Agentic AI Engineer.

 Python Foundations for AI

  • Introduction to Python
  • Variables and Data Types
  • Operators
  • Conditional Statements and Loops
  • Functions & Classes
  • Dictionaries and Sets
  • Modules, Files

  • Pandas
  • Numpy
  • Matplotlib
  • Pydantic
  • Uv Package manager
  • Fast API
  • Building REST API
  • Database operations

Developing AI Solutions using Azure AI (AI-102)

  • Introduction to AI with Azure
  • Understanding Machine Learning
  • Introduction to Deep Learning
  • Types of Machine Learning
  • Gen AI and LLMs
  • Azure AI Services Offering
  • Prepare to develop AI solutions on Azure
  • Create and consume Azure AI services
  • Monitor Azure AI services

  • Analyze images using pre-trained models
  • Classify images with custom models
  • Detect and analyze faces
  • Perform OCR on text in images
  • Analyze videos using Azure Video Indexer
  • Analyze text with Azure AI Language
  • Create question-answering solutions
  • Translate text and speech using Azure AI Translator
  • Create an Azure AI Search solution
  • Maintain and optimize Azure AI Search solutions
  • Use prebuilt models to analyze common documents
  • Extract data using Azure Document Intelligence

OpenAI and GenAI Tools

  • Generative AI Fundamentals
  • Generative AI vs. Traditional AI
  • Large Language Models (LLMs)
  • Prompt Engineering
  • Introduction to Azure OpenAI Service
  • Build NLP solutions.
  • Apply prompt engineering.
  • Generate code and images.
  • Implement Retrieval-Augmented Generation (RAG).

  • Understanding OpenAI and ChatGPT
  • How ChatGPT Works?
  • Coding with ChatGPT
  • Generating, optimizing, and debugging code
  • Generating documentation and code explainability
  • Translation among different programming languages
  • What is GitHub Copilot?
  • Setting up GitHub Copilot
  • GitHub Copilot Basics and Features
  • Debugging and optimization tips
  • Testing and Debugging with GitHub Copilot

 Azure Gen AI and LLMs

    • What is Azure AI Foundry?
    • Use cases and benefits
    • Accessing Azure AI Foundry
    • Connecting compute, data, and other resources
    • Working with Azure Foundry
    • Connecting to data sources (Blob Storage, Azure SQL etc.)
    • Dataset versioning and management
    • Data labeling and preparation
    • Responsible AI considerations in data
    • Models in Azure Foundry
    • Foundation models vs custom models
    • Using Azure OpenAI models (GPT, DALL·E)
    • Fine-tuning and prompt engineering
    • Uploading and using custom models (HuggingFace, etc.)

    • Experimentation & Evaluation
    • Building and running training pipelines (SDK + UI)
    • Hyperparameter tuning and metrics tracking
    • Evaluation & Responsible AI Tools
    • Model evaluation and bias detection
    • Compliance and audit features in Foundry
    • Deploying models with managed endpoints
    • Secure API access and authentication
    • Scaling and monitoring deployments
    • Integrations & Workflows
    • Integrating with Teams, Power BI
    • Using Foundry APIs and SDKs (Python + REST)

 Agentic AI: Multi Agents & MCP Servers

  • Agents 101: Roles, collaboration models, and 2025 trends
  • Introducing Microsoft Agent Framework
  • Working with Microsoft Agent Framework
  • Error Handling: Recovery flows and validation agents
  • Build a multi agent workflow

  • MCP Architecture: Servers, clients, and communication patterns
  • Enterprise Data Integration: SQL Server, Blob Storage, Cosmos DB or SharePoint
  • Security & Performance: Authentication, caching, and scaling MCP services
  • MCP-enabled workflow with enterprise system integration

Career Transformation & Tech Leadership (Only with Live Training Plus)

  • Personalized Career Coaching
  • Physical & Mental Fitness
  • Secrets of Time Management
  • Success Habits
  • Secrets of Productivity
  • Build projects portfolio on GitHub
  • Make your Projects Live
  • Draft your Resume
  • Make Profile on Job Portals
  • Art of unlocking opportunities
  • Prepare Yourself for interview
  • How to answer tough questions
  • Learn How to Face your tech interview

  • Meeting Room Etiquette
  • Focus Activity (Session Start)
  • Pleasant Face & Confident Smile
  • Clear & Confident Communication
  • Impact of Greetings
  • Inspirational Quotes
  • Personality & Presence
  • Using the Right Professional Tools
  • Hand & Body Gestures
  • Speaking Practice
  • Presentation Skills
  • Mic & Device Handling
  • Growth Mindset & Self-Improvement
  • Building High-Performance Teams
  • Delegation & Team Empowerment
  • Culture of Innovation
1. Azure AI: Exploring Form Recognition
30 min
2. Azure AI: Use an Azure AI Services Container
45 min
3. Azure AI: Read Text in Images
1 hr
4. Azure AI: Ubuntu Data Science VM ARM Template
45 min
5. Azure AI: Deploy AI Search using Bicep
30 min
6. Azure AI: Translate Text with Azure AI Translator
45 min
7. Azure AI: AI Sensor Data Preprocessing using NumPy
30 min
8. Azure AI: Validate AI Configuration Input using Pydantic
30 min
9. Azure AI: Analyze Azure AI Service Logs with Pandas
30 min
10. Azure AI: Recognize and Synthesize Speech
45 min
11. Azure AI: Building Azure AI Health Bot using Azure CLI
30 min
12. Azure AI: Deploy AI Search using an ARM Template
30 min
13. Azure AI: Text Analysis with Azure AI Content Safety
45 min
14. Azure AI: Image Analysis with Azure AI Content Safety
45 min
15. Azure AI: Explore Computer Vision
30 min
16. Azure AI: Create a Knowledge Store with Azure AI Search
1 hr
17. Azure AI: Multilingual Speech Translation
45 min
18. Azure AI: Pandas with Azure Text Analytics Results
30 min
19. Azure AI: Exploring Face Detection
45 min
20. Azure AI: Create a FastAPI Service for AI Translation
30 min
21. Azure AI: FastAPI Service for NumPy Model Predictions
30 min
22. Azure AI: Validate Input Text & Metadata with Pydantic
30 min
23. Azure AI: Exploring Optical Character Recognition
45 min
24. Azure AI: Preprocess Data & Send to Azure AI
30 min
25. Azure AI: Extract Data from Forms
1 hr
26. Azure AI: Translate Speech using Azure AI Speech Service
1 hr
27. Azure AI: Pydantic JSON Schema for Azure AI Settings
30 min
28. Azure AI: AI Image Captioning API with FastAPI
30 min
29. Azure AI: Detect and Analyze Faces
1 hr
30. Prime Number Generator
30 min
31. Prime Number Generator
30 min
32. Temperature Converter Module
30 min
33. CSV Reader and Filter
30 min
34. Library Book Management System
30 min
35. Custom Calculator with Error Handling
30 min
36. Email Validator
30 min
37. Email Validator
30 min
38. Data Cleaner with map, filter, and lambda
30 min
39. Parallel File Download Simulation
30 min
40. Simple Weather API Fetcher
30 min
41. Logging Decorator
30 min
42. Azure AI Foundry: Generative AI Fundamentals with Azure OpenAI
30 min
43. Azure AI Foundry: Exploring and Comparing Different LLMs
45 min
44. Azure AI Foundry: Responsible AI with Azure OpenAI
35 min
45. Azure AI Foundry: Prompting with Azure AI
30 min
46. Azure AI Foundry: Building Layered AI Prompts
45 min
47. Azure AI Foundry: Building Chat Applications
45 min
48. Azure AI Foundry: Generate Images with Azure DALL·E in Python
50 min
49. Azure AI Foundry: Text Generation Apps
30 min
50. Azure AI Foundry: Mini Search Engine with Azure AI & Python
45 min
51. Azure AI Foundry: AI Weather App with Function Calling
50 min
52. Azure AI Foundry: AI Chat App with Azure OpenAI & Flask
30 min
53. Azure AI Foundry: Conversational App with Flask & OpenAI
40 min
54. Azure AI Foundry: Generative AI Application Lifecycle
50 min
55. Azure AI Foundry: RAG AI Chat App with Azure & Flask
45 min
56. Azure AI Foundry: AI Policy Reviewer with Flask & Azure
50 min
57. Azure AI Foundry: AI Policy Reviewer with Azure Agents
55 min
58. Azure AI Foundry: SLM App with Azure OpenAI & Flask
40 min
59. Azure AI Foundry: Fine-Tuned AI Assistant with Azure & Flask
45 min
60. Azure AI Foundry: Low-Code AI App with Azure & Flask
40 min
61. Azure AI Foundry: LLaMA Chat App with Hugging Face & Flask
50 min
1. Introduction to AI Workloads and Azure AI Capabilities
10 questions
2. Scope and Objectives of the AI-102 Certification
10 questions
3. Responsible AI Principles: Fairness, Safety, Privacy, Accountability
10 questions
4. Azure AI Content Safety and Responsible Usage
10 questions
5. Monitoring AI for Bias and Drift
10 questions
6. Azure Generative AI Overview & Core Concepts
10 questions
7. Introduction to Azure AI Foundry Platform
10 questions
8. Hubs, Projects & Workspaces Architecture
10 questions
9. Azure AI Studio Features
10 questions
10. Identity, Access Control & Responsible AI Essentials
10 questions
11. Azure Model Catalog for Gen AI
10 questions
12. Smart Model Selection for Modern AI Workloads
10 questions
13. Deploying Models: Cloud, Edge & Hybrid
10 questions
14. Model Evaluation, Testing, Tuning & Versioning
10 questions
15. Running Local LLMs with Docker & Transformers
10 questions
16. Creating and Consuming Azure AI Services (Language, Vision, Speech, Search)
10 questions
17. Securing AI Services (Authentication, Authorization, Network Security)
10 questions
18. Monitoring and Logging with Application Insights
10 questions
19. Integrating AI Services using CLI, SDKs, and REST APIs
10 questions
20. Cost Management and Governance for AI Projects
10 questions
21. Image Analysis with Prebuilt and Custom Vision Models
10 questions
22. Object and Face Detection in Images
10 questions
23. Optical Character Recognition (OCR) for Text Extraction
10 questions
24. Video Analysis (Real-Time and Batch)
10 questions
25. Deploying Vision Models to Edge Devices
10 questions
26. Prompt Engineering Fundamentals
10 questions
27. Advanced Prompting (Layered Techniques)
10 questions
28. Building LLM Workflows with Prompt Flow
10 questions
29. Function Calling, Tools & External APIs
10 questions
30. Error Handling, Guardrails & Quality Controls
10 questions
31. RAG Architecture & Core Principles
10 questions
32. Document Ingestion & Preprocessing
10 questions
33. Embedding Strategies & Models
10 questions
34. Vector Databases (Azure Search, Pinecone, Redis)
10 questions
35. Latency, Ranking & Optimization
10 questions
36. Text Analytics: Sentiment, Key Phrases, Named Entities
10 questions
37. Custom Text Classification and Entity Recognition
10 questions
38. Conversational Language Understanding (CLU)
10 questions
39. Question Answering with Azure AI Language
10 questions
40. Text Translation and Language Detection
10 questions
41. Speech-to-Text and Text-to-Speech Conversion
10 questions
42. Custom Speech Model Training
10 questions
43. Real-Time Captions and Speech Translation
10 questions
44. Voice Synthesis using Custom Neural Voice (CNV)
10 questions
45. Secure and Monitor Speech Services
10 questions
46. Intelligent Agent Fundamentals
10 questions
47. Microsoft Agent Framework
10 questions
48. Copilot & Agent-Orchestrated Workflows
10 questions
49. Multi-Agent Collaboration Models
10 questions
50. Validation Agents & Error Recovery
10 questions
51. MCP Architecture
10 questions
52. Building MCP Services
10 questions
53. Enterprise Data Integration
10 questions
54. Scaling, Authentication & Secure Context Sharing
10 questions
55. Azure OpenAI Capabilities and Use Cases
10 questions
56. Prompt Engineering and Fine-Tuning GPT Models
10 questions
57. Building Apps with ChatGPT and GPT APIs
10 questions
58. Retrieval Augmented Generation (RAG)
10 questions
59. Image Generation using DALL·E
10 questions
60. Azure AI Search Architecture and Components
10 questions
61. Indexing Structured and Unstructured Data
10 questions
62. AI Enrichment with Cognitive Skills
10 questions
63. Semantic and Vector Search Implementation
10 questions
64. Integration with Azure OpenAI for RAG
10 questions
65. Responsible AI Policies & Compliance
10 questions
66. Observability, Monitoring & Telemetry
10 questions
67. Planning Document Intelligence Solutions
10 questions
68. Prebuilt and Custom Document Model Usage
10 questions
69. Training and Testing Models with Sample Forms
10 questions
70. Composing and Chaining Multiple Models
10 questions
71. Large-Scale Document Processing
10 questions
1. Functions in Python
6 min
2. Lambda Functions in Python
4 min
3. Recursion in Python
5 min
4. Modules and Packages in Python
4 min
5. Object-Oriented Programming (OOP) with Python
7 min
6. Introduction to Python
6 min
7. Variables & Data Types in Python
5 min
8. Operators in Python
4 min
9. Conditional Statements in Python
3 min
10. Conditional Statements in Python
3 min
11. Loops in Python
2 min
12. Loops in Python
2 min
13. Jump Statements in Python
3 min
14. Jump Statements in Python
3 min
15. Introduction to AI Workloads and Azure AI Capabilities
7 min
16. Scope and Objectives of the AI-102 Certification
7 min
17. Responsible AI Principles
6 min
18. Azure AI Content Safety
8 min
19. Monitoring AI for Bias and Drift
8 min
20. Creating and Consuming Azure AI Services
5 min
21. Securing AI Services
6 min
22. Monitoring and Logging with Application Insights
8 min
23. Integrating AI Services using CLI, SDKs, and REST APIs
4 min
24. Cost Management and Governance for AI Projects
7 min
25. Image Analysis with Prebuilt and Custom Vision Models
8 min
26. Object and Face Detection in Images
9 min
27. Optical Character Recognition (OCR) for Text Extraction
6 min
28. Video Analysis in Azure AI
7 min
29. Deploying Vision Models to Edge Devices
5 min
30. Text Analytics in Azure AI
8 min
31. Custom Text Classification and Entity Recognition
6 min
32. Conversational Language Understanding (CLU) in Azure AI
6 min
33. Text Translation and Language Detection in Azure AI
6 min
34. Speech-to-Text and Text-to-Speech Conversion in Azure AI
7 min
35. Custom Speech Model Training in Azure AI
9 min
36. Real-Time Captions and Speech Translation in Azure AI
6 min
37. Voice Synthesis using Custom Neural Voice (CNV) in Azure AI
7 min
38. Secure and Monitor Speech Services in Azure AI
5 min
39. Azure OpenAI Capabilities and Use Cases
7 min
40. Prompt Engineering and Fine-Tuning GPT Models in Azure AI
9 min
41. Retrieval Augmented Generation (RAG) in Azure AI
8 min
42. Image Generation using DALL·E in Azure AI
6 min
43. Azure AI Search Architecture and Components
6 min
44. Semantic and Vector Search Implementation in Azure AI
5 min
45. Prebuilt and Custom Document Model Usage in Azure AI
8 min
46. Introduction to Azure AI Foundry
11 min
47. Adoption of Generative AI Through Azure AI Foundry
8 min
48. Architectural Overview of Azure AI Foundry
7 min
49. Features and Capabilities of Azure AI Studio
8 min
50. Exploring the AI Model Catalog in Azure AI Foundry
8 min
51. Identity and Access Management in Azure AI Foundry
10 min
52. Responsible AI and Compliance Features in Foundry
6 min
53. Observability and Performance Monitoring Tools in Azure AI Foundry
13 min
54. Using the Azure AI Foundry SDK and Command-Line Tools
7 min
55. Automating AI Workflows Using Prompt Flow and Pipelines
8 min
56. Implementing CI/CD Pipelines for AI Model Deployment
13 min
57. File Handling in Python
4 min
58. Errors & Exception Handling in Python
9 min
  1. Introduction to Azure AI and Responsible AI
15 questions
  2. Azure AI Skill Test
30 questions
  3. Developing and Managing Azure AI Services
15 questions
  4. Computer Vision Solutions with Azure AI Vision
15 questions
  5. Natural Language Processing (NLP) with Azure AI Language
15 questions
  6. Speech Services with Azure AI
15 questions
  7. Generative AI with Azure OpenAI Service
15 questions
  8. Knowledge Mining with Azure AI Search
15 questions
  9. Introduction to Azure AI Foundry
15 questions
  10. Azure AI Foundry Architecture and Core Services
15 questions
  11. Azure AI Foundry Data Management and Integration
15 questions
  12. Azure AI Foundry Model Deployment and Monitoring
15 questions
  13. Azure AI Foundry Security, Networking, and Governance
15 questions
  14. Azure AI Foundry Developer Tools and Ecosystem Integration
15 questions
DOWNLOAD DETAILED CURRICULUM

Azure Cloud AI Architect Career Scope

₹32.5 LPA
Avg package
44%
Avg hike
1000+
Tech transitions

Annual Average Salaries

2.5k
2k
1.5k
1k
0k
Min(14L)
Avg(32L)
Max(40L)
Demand
Demand
6K+
Jobs Opening
₹30.5 LPA
Avg package
46%
Avg hike
4000+
Tech transitions

Annual Average Salaries

2.5k
2k
1.5k
1k
0k
Min(14L)
Avg(32L)
Max(45L)
Demand
Demand
5K+
Jobs Opening
₹29.9 LPA
Avg package
48%
Avg hike
2000+
Tech transitions

Annual Average Salaries

2.5k
2k
1.5k
1k
0k
Min(14L)
Avg(32L)
Max(50L)
Demand
Demand
5.5K+
Jobs Opening
₹ 31.9 LPA
Avg package
48%
Avg hike
3000+
Tech transitions

Annual Average Salaries

2.5k
2k
1.5k
1k
0k
Min(14L)
Avg(30L)
Max(50L)
Demand
Demand
6.5K+
Jobs Opening
₹32 LPA
Avg package
44%
Avg hike
3000+
Tech transitions

Annual Average Salaries

2.5k
2k
1.5k
1k
0k
Min(14L)
Avg(32L)
Max(45L)
Demand
Demand
4.7K+
Jobs Opening

Tools and Technologies Covered

Python
Fast API
Azure AI Services
Azure AI Foundry
Azure Vision
Azure Search
Azure Face API
Language
Open AI
Copilot
LLMs
MCP Server
LLama Model
GPT
DeepSeek
Phi Model
AI Agents
GitHub Copilot
CI/CD

What can you accomplish at the end of training?

Transform Your Career: Become an Azure Cloud AI Architect!

  •  Boost Your Salary – Earn up to ₹45 LPA
  •  Design Scalable AI Solutions with Azure, Python and AI
  •  Earn Global Azure Certifications (AI-900, AI-102)
  •  Master Cutting-Edge AI Technologies – Python, Azure AI, Gen AI & More
  •  Build Real-world Projects for chatbot, sales forecasting & fraud detection projects
  •  Ace Your Azure Cloud AI Architect Interviews

🚀 Take the next step to become a job-ready Azure Cloud AI Architect today!

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Our learn-by-building-project method enables you to build practical/coding experience that sticks. 95% of our learners say they have confidence and remember more when they learn by building real world projects.

Azure AI, Gen AI & Agentic AI Engineer Certification Training Program

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Course Mentors

Shailendra Chauhan
10X MICROSOFT MVP AI ARCHITECT

Shailendra Chauhan

Microsoft MVP, Founder & CEO at ScholarHat

17+ Years of Industry Experience as Mentor & Solution Architect
Expert in .NET, Angular, React & Python
Azure Cloud & AI/ML/Gen AI Specialist
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Pranit Thakur

Technical Consultant and Corporate Trainer

12+ Years Technical & Corporate Training
Expert in React, Angular & Node.js
Passionate Technology Trainer & Mentor
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Rahul Kumar

Author and .NET Tech Lead

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Frequently Asked Questions

Q1. What is the Azure ML Certification Course?
The Azure ML Certification Course is a specialized training program focused on teaching you how to design and implement machine learning solutions using Microsoft Azure. You will learn how to leverage Azure Machine Learning services, build machine learning models, and deploy AI-driven solutions to tackle real-world business problems. This course is ideal for aspiring AI Engineers, Data Scientists, or professionals looking to enhance their machine learning skills within the Azure ecosystem.
Q2. What are the prerequisites for enrolling in the Azure AI/ML Certification Course?
Before enrolling in the Azure AI ML Certification course, it's beneficial to have: 1.) A basic understanding of cloud computing and Azure services. 2.) Familiarity with programming languages like Python and R. 3.) Knowledge of basic machine learning concepts and data science. While prior experience is helpful, it's not a strict requirement. If you're new to AI/ML, the course will provide you with the foundational knowledge needed to start your journey in Azure machine learning.
Q3. What skills will I gain from the Azure Machine Learning Certification Course?
Upon completing the Azure Machine Learning Certification course, you will: 1.) Understand the core Azure Machine Learning services and how to use them for building models. 2.) Gain hands-on experience in data preprocessing, model training, and evaluation. 3.) Learn to implement AI solutions using Azure Cognitive Services and Azure Databricks. 4.) Master the deployment and monitoring of machine learning models, ensuring they are scalable and reliable in production. 5.) Be equipped to solve real-world machine learning challenges with practical experience in the Azure ecosystem.
Q4. How does the Azure ML Certification Course prepare me for certifications?
The Azure ML Certification course is aligned with the requirements for the Azure AI Engineer Associate certification (exam AI-102). The course provides: 1.) A structured curriculum covering key skills and topics tested in the certification exam. 2.) Real-life case studies and practical exercises to deepen your understanding. 3.) Detailed exam preparation, including practice questions, tips, and insights into the exam format. By the end of the course, you will be fully prepared to tackle the Azure AI ML certification exam with confidence.
Q5. What career opportunities are available after completing this course?
After completing the Azure Machine Learning Certification, you can pursue roles such as: 1.) Azure AI Engineer 2.) Machine Learning Engineer 3.) Data Scientist 4.) AI Researcher 5.) Azure Solutions Architect The growing adoption of AI and machine learning across industries means that professionals with Azure ML certification are in high demand. Completing this certification can significantly enhance your career prospects and open doors to lucrative positions at companies like Microsoft, Google, Amazon, Accenture, and more.
Q6. How long does it take to complete the Azure Machine Learning Certification Course?
The duration of the Azure Machine Learning Certification course typically ranges from 4 to 6 weeks, depending on your learning pace. If you opt for a self-paced course, you can complete it in less time by dedicating more hours each week. A structured, instructor-led course may take slightly longer. 1.) On average, the course involves 20 to 30 hours of training content, including theory and hands-on labs. 2.) The time commitment may vary based on the depth of the course and whether you are combining it with other studies or work responsibilities. By the end of the course, you will have acquired practical skills in Azure Machine Learning, ready to take the certification exam.
Q7. Is this course suitable for beginners in AI and ML?
Yes, the Azure AI/ML Certification Course is suitable for beginners in AI and ML. Although some basic knowledge of cloud computing and programming is helpful, the course provides the foundational knowledge needed to get started in Azure machine learning. 1.) The course starts with introductory topics and gradually progresses to more advanced concepts, ensuring a smooth learning curve. 2.) If you're new to AI and ML, the course offers the perfect opportunity to build a solid understanding of the core concepts and hands-on practice in Azure machine learning. You’ll learn at your own pace, and by the end of the course, you'll be well-equipped to tackle real-world machine learning challenges.
Q1. Can I Attend a Demo Session before Enrolment?
Yes, you can Attend a Demo Session before Enrolment in angular certification course. It gives you the opportunity to assess whether the training program aligns with your learning objectives. So, don't hesitate! Take advantage of this opportunity and attend a demo session before making your decision.
Q2. Can I request for a support session if I need to better understand the topics?
Yes, of course you can request for a support session if you need to better understand the topics. For that, you need to be in touch with the counsellor. Contact on +91- 999 9123 502 or you can mail us at hello@scholarhat.com
Q3. Who are your mentors?
All our mentors are highly qualified and experience professionals. All have at least 8-10 yrs of development experience in various technologies and are trained by ScholarHat to deliver interactive training to the participants.
Q4. What If I miss my online training class?
All online training classes are recorded. You will get the recorded sessions so that you can watch the online classes when you want. Also, you can join other class to do your missing classes.
Q5. Can I share my course with someone else?
In short, no. Check our licensing that you agree to by using ScholarHat LMS. We track this stuff, any abuse of copyright is taken seriously. Thanks for your understanding on this one.
Q6. Do you provide any course material or live session videos?
Yes we do. You will get access to the entire content including class videos, mockups, and assignments through LMS.
Q7. Do you provide training on latest technology version?
Yes we do. As the technology upgrades we do update our content and provide your training on latest version of that technology.
Q8. Do you prepare me for the job interview?
Yes, we do. We will discuss all possible technical interview questions and answers during the training program so that you can prepare yourself for interview.
Q9. Will I get placement assistance after receiving my course completion certificate?
Yes, you’ll get placement assistance after receiving your course completion certificate. The placement assistance provided by the US will guide you through the job search process, help you polish your resume, and connect you with potential employers. For that, you need to be in touch with the counsellor. Contact on +91- 999 9123 502 or you can mail us at hello@scholarhat.com
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