Microsoft Certified Training Program

Azure AIML Job-Oriented Program with 4 Certifications

Master Microsoft Azure AI & Machine Learning with comprehensive training designed for career success. Get certified, get hired, and advance your AI/ML career with industry-recognized credentials. 

10 Weeks

Intensive Training

Live Sessions

Expert Instructors

100% Job

Placement Support

4 Certificates

Microsoft Official

4.5 ( 141 Ratings )
Learners
40000 +

About Our Course

The Azure AIML Job-Oriented Program with 4 Certifications is your step-by-step path to becoming job-ready in Microsoft Azure AI & Machine Learning. You’ll start with the basics and move into machine learning, deep learning, AI models, and data science—all while working on real-world projects and hands-on labs. Along the way, you’ll prepare for four of the most in-demand Microsoft certifications (AI-900, AI-102, DP-100, and AZ-900). By the end, you won’t just have certifications—you’ll have the practical skills and confidence to land roles like AI Engineer, Data Scientist, Machine Learning Engineer, or Azure AI Architect. 

Who Should Enroll in This Program?

IT Professionals

Looking to upgrade their skills and transition into roles like Azure AI Engineer, Machine Learning Engineer, or AI Architect.

Software Developers

Interested in learning how to build and deploy machine learning models and integrate AI into applications using Azure AI services.

Cloud Engineers & Data Scientists

Aiming to strengthen their expertise in AI/ML, data science, and Azure AI tools.

Fresh Graduates & Career Switchers

Eager to enter the high-demand AI/ML field with a structured, job-ready training path.

Aspiring AI Engineers

Who wants to start a career in Azure AI & Machine Learning with globally recognized certifications?

Tools Covered

Key Outcomes of This Program

4 Globally Recognized Certifications

Earn Microsoft credentials (AI-900, AI-102, DP-100, and AZ-900) that validate your expertise and make your resume stand out to employers.

Hands-On Experience

Gain practical skills by working directly on Azure AI tools like Azure ML Studio, Cognitive Services, Azure AI Foundry, AI Agents, and more.

Real-World Projects

Build a portfolio with projects that mirror real industry scenarios, giving you proof of work that hiring managers look for.

Job-Ready Skills

Master high-demand AI/ML skills, including model building, training, evaluation, and deployment using Azure’s powerful cloud-based tools.

Career Support & Extras

Go beyond technical learning with personalized resume reviews, LinkedIn profile optimization, and mock interviews so you can confidently showcase your skills and secure offers.

Expert Mentorship & Lifetime Access

Get 24/7 support from certified Azure AI/ML experts, plus lifetime access to course content and updates so you never fall behind.

60+ Labs

Practice Labs

100+ Videos

Video Course

8 Projects

Projects Course

250+ QA's

Q&A Exams

Course Break-Down

Lessons:
  • Lesson 1: Fundamental AI Concepts
  • Lesson 2: Fundamentals of Machine Learning
  • Lesson 3: Azure Machine Learning
  • Lesson 4: Supervised vs. Unsupervised Learning
  • Lesson 5: Deep Learning & Neural Networks
  • Lesson 6: Feature Engineering
  • Lesson 7: Hyperparameter Tuning
  • Lesson 8: MLOps on Azure
Labs:
  • Lab 1: Explore Automated ML in Azure ML
  • Lab 2: Explore Azure AI Services
  • Lab 3: Work with Compute Resources in AML
  • Lab 4: Work with Environments in AML
Lessons:
  • Lesson 1: Fundamentals of Generative AI
  • Lesson 2: Introduction to Azure OpenAI Service
  • Lesson 3: Provision an Azure OpenAI resource
  • Lesson 4: Large Language Models (LLMs)
  • Lesson 5: Azure OpenAI Studio
  • Lesson 6: Tokenization in Generative AI & LLM
Labs:
  • Lab 1: Generate images with AI
  • Lab 2: Prepare for an AI development project
  • Lab 3: AI Foundry: Deploy & Compare Language Models
Lessons:
  • Lesson 1: AI Agents Basics
  • Lesson 2: Building Agents
  • Lesson 3: Autonomous Agents & Multimodal AI
  • Lesson 4: Real-World Applications
  • Lesson 5: Semantic Kernel
  • Lesson 6: Agentic AI
Labs:
  • Lab1: Explore AI Agent development
  • Lab 2: Develop an AI agent
  • Lab 3: Use a custom function in an AI agent
  • Lab 4: Develop a multi-agent sol. with AI Foundry
  • Lab 5: Connect AI agents to tools using MCP
  • Lab 6: Azure AI agent with the Semantic Kernel
  • Lab 7: Connect to remote agents with A2A protocol
  • Lab 8: Build an Azure AI Chat Agent with Microsoft SDK
  • Lab 9: Multi-Agent Solution with Microsoft Framework
Lessons:
  • Lesson 1: Introduction
  • Lesson 2: Analyzing Text
  • Lesson 3: Translating Text
  • Lesson 4: Create Question-Answering Solutions
  • Lesson 5: Conversational Language Model
  • Lesson 6: Custom Text Classification
  • Lesson 7: Custom Named Entity Recognition
  • Lesson 8: Speech Recognition
  • Lesson 9: Azure AI Search
Labs:
  • Lab 1: Analyze Text with Azure AI Search
  • Lab 2: Create a Question Answering Solution
  • Lab 3: Create a Language Understanding Model
  • Lab 4: Custom Text Classification using AI Language
  • Lab 5: Extract Custom Entities
  • Lab 6: Translate Text with the Azure AI Translator
  • Lab 7: Create Speech-Enabled App: Azure AI Speech
  • Lab 8: Translate Speech with Azure Speech Resource
  • Lab 9: Develop an Audio-Enabled Chat App
  • Lab 10: Explore the Voice Live API
Lessons:
  • Lesson 1: Fundamentals of Computer Vision
  • Lesson 2: Computer Vision Capabilities in Azure
  • Lesson 3: Image Analysis – Azure AI Vision
  • Lesson 4: Detecting Faces with Azure AI Vision
  • Lesson 5: Image Classification with Azure AI Vision
  • Lesson 6: Analyzing Videos Using Video Indexer
Labs:
  • Lab 1: Analyze Images with Azure AI Vision
  • Lab 2: Classify Images with AI Vision Custom Model
  • Lab 3: Detect Objects in Images with Custom Vision
  • Lab 4: Detect and Analyze Faces
  • Lab 5: Read Text in Images
  • Lab 6: Analyze Video With Video Indexer
  • Lab 7: Classify Images with Azure AI Custom Vision
Lessons:
  • Lesson 1: Azure AI Document Intelligence Solution
  • Lesson 2: Analyze Document Using Custom Model
  • Lesson 3: Custom Skill for Azure AI Search
  • Lesson 4: Knowledge Store with Azure AI Search
  • Lesson 5: Implementing an Intelligent Search Solution
Labs:
  • Lab 1: Extract Information from Multimodal Content
  • Lab 2: Develop a Content Understanding Client App
  • Lab 3: Analyze Forms with Prebuilt Azure AI Document
  • Lab 4: Analyze Forms with Custom Azure AI Document
  • Lab 5: Create a Knowledge Mining Solution
Lessons:
  • Lesson 1: Transformer Mechanics
  • Lesson 2: Transformers Advantages and Limitations
  • Lesson 3: Encoder-Decoder Architecture
  • Lesson 4: Positional Encoding & Attention Mechanisms
  • Lesson 5: Advanced LLMs
  • Lesson 6: Evolution of Models (BERT → GPT-4 → T5)
Labs:
  • Lab 1: Fine-Tune a Language Model
  • Lab 2: Create generative AI app that use your data
  • Lab 3: Using Advanced Prompt Techniques
Lessons:
  • Lesson 1:What is Azure AI Foundry
  • Lesson 2: Microsoft Azure AI Foundry & Deploy Models
Labs:
  • Lab 1: Create a Gen AI Chat App
  • Lab 2: Develop a Multimodal Generative AI App
  • Lab 3: Manage Chat Conversation with Prompt Flow
  • Lab 4: Use Prompt Flow for NER in AI Foundry Portal
  • Lab 5: Explore Content Filters in Azure AI Foundry
  • Lab 6: Evaluate Generative AI Performance
Lessons:
  • Lesson 1: Retrieval Augmented Generation
  • Lesson 2: Use Your Own Data with Azure OpenAI
Labs:
  • Lab 1: Add Your Data for RAG with Azure OpenAI Service
Lessons:
  • Lesson 1: Microsoft Copilot Ecosystem & AI Tools
  • Lesson 2: Copilot Studio Overview & Interface
  • Lesson 3: Topic Management & Copilot Design
  • Lesson 4: Publishing & Testing Copilots
  • Lesson 5: Entities, Variables & Customization
  • Lesson 6: Configuring Data Sources & Actions
  • Lesson 7: Copilot Studio + Power Platform Integration
  • Lesson 8: Boosting Copilot NLU & AI Models
  • Lesson 9: Copilot Management & Advanced Capabilities
  • Lesson 10: Connectors, Actions & Extensions
  • Lesson 11: Voice-Enabled Copilots
  • Lesson 12: Performance Analysis & Security
  • Lesson 13: Responsible AI in Copilot Studio
Labs:
  • Lab 1: Explore Microsoft Copilot in Microsoft Edge
Lessons:
  • Lesson 1: Explore Core Data Concepts
  • Lesson 2: Data roles and services
  • Lesson 3: Intro to Azure Data Lake Storage Gen2
  • Lesson 4: Introduction to Azure Synapse Analytics
  • Lesson 5: Use Azure Synapse serverless SQL pool
  • Lesson 6: Use Azure Synapse serverless SQL pools
  • Lesson 7:Create a lake DB in AZ Synapse Analytics
Lessons:
  • Lesson 1: Analyze Data with Apache Spark in Azure Synapse
  • Lesson 2: Transform Data with Spark in Azure Synapse Analytics
  • Lesson 3: Use Delta Lake in Azure Synapse Analytics
  • Lesson 4: Analyze Data in a Relational Data Warehouse
  • Lesson 5: Load Data into a Relational Data Warehouse
  • Lesson 6: Build a Data Pipeline in Azure Synapse Analytics
  • Lesson 7: Use Spark Notebooks in an Azure Synapse Pipeline
Lessons:
  • Lesson 1: Training Models with Designer
  • Lesson 2: Introduction to Compute
  • Lesson 3: Working with Environments
  • Lesson 4: Publishing Models with Designer
  • Lesson 5: Working with Compute Targets
  • Lesson 6: Introduction to Experiments
  • Lesson 7: Training and Registering Models
  • Lesson 8: Hyperparameter Tuning
Labs:
  • Lab 1: Run a Training Script as a Command Job in Azure ML
  • Lab 2: Tracking ML Training Jobs with MLflow
  • Lab 3: Perform Hyperparameter Tuning with Sweep Job
  • Lab 4: Run Pipelines in Azure Machine Learning
Lessons:
  • Lesson 1: Design a Model Deployment Solution
  • Lesson 2: Working with Datastores and Datasets
  • Lesson 3: Logistic Regression Algorithm
  • Lesson 4: Confusion Matrix
  • Lesson 5: ROC Curve and Area Under Curve
  • Lesson 6: Normalization
Labs:
  • Lab 1: Deploy a Model to a Managed Online Endpoint
  • Lab 2: Deploy a Model to a Batch Endpoint
Lessons:
  • Lesson 1: What is MLOps?
  • Lesson 2: MLOps Stages
Labs:
  • Lab 1: Model Registration and Versioning with MLflow
  • Lab 2: Install & Use DVC with Azure Storage
  • Lab 3: Model Deployment with Azure & Gradio
Lessons:
  • Lesson 1: Risk of Generative AI
  • Lesson 2: Core Dimensions of Responsible AI
  • Lesson 3: Implement Responsible Generative AI
  • Lesson 4: Security Compliance and Governance

Project works

Project 1: Chatbot Using Azure AI Search and OpenAI

In this project, you will integrate Azure AI Search and OpenAI to build a context-aware chatbot. You'll set up essential services, upload data, and train the model to deliver intelligent and accurate responses based on user queries.

Project 2: Synthetic Data Generation with LLM

Explore Synthetic Data Generation using Large Language Models (LLMs) in this project. You will set up your environment, create prompts for inference, and build a synthetic dataset with generated labels using Azure ML endpoints.

Project 3: Building RAG Application With Langchain

Learn to build a Retrieval-Augmented Generation (RAG) application with Langchain and Azure OpenAI. This project involves setting up Azure resources, integrating retrieval and generation mechanisms, and testing the application to ensure optimal performance.

Project 4: Crafting Smart Ads with AI

In this project, you'll use Azure Cosmos DB and AI algorithms to create personalized ads at scale. You will analyze user data and generate dynamic, targeted ad content to increase engagement and drive better results.

Project 5: Multimodal RAG Agents Using Azure OpenAI

Develop Multimodal RAG Agents using Azure OpenAI in this project. You'll learn how to combine different AI techniques to build agents that can handle text and images, enhancing their capability to provide context-driven responses.

Project 6: Movie Recommender with Azure ML

Build a Movie Recommendation System with Azure ML using Singular Value Decomposition (SVD). You'll work with a user ratings dataset to create personalized movie recommendations and deploy the model for real-time predictions.

Project 7: Predicting Diabetes Using Azure ML

Create a predictive model for diabetes using Azure Machine Learning. You’ll set up an Azure ML workspace, create a dataset, and run AutoML experiments to identify the best model for accurate predictions of diabetes risk.

Project 8: Housing Price Prediction with Azure ML

Develop a Housing Price Prediction model using Azure ML. You’ll set up a workspace, create datasets, and run an AutoML experiment to build and deploy a predictive model for accurate housing price forecasts.

Project 9: University Admission Using Azure ML Studio

In this project, you’ll build a machine learning model to predict university admissions using Azure ML Studio. You will create datasets, run AutoML jobs, and deploy the model to predict admission outcomes based on key factors.

Project 10: Credit Card Fraud Detection with Azure ML

Learn how to detect credit card fraud using Azure ML. You will work with transaction data to create a dataset, run an AutoML experiment, and develop a model to accurately identify fraudulent credit card activities.

Skills You Need to Get Started

No Prior Experience Required

The program starts with the fundamentals, making it suitable for beginners.

AI & ML Fundamentals First

Gain a strong foundation in AI, Machine Learning, Deep Learning, and Generative AI before diving into specialized topics.

Step-by-Step Learning

Start with Azure AI & Machine Learning basics, then advance your skills in building, training, and deploying AI models using Azure’s powerful tools.

Hands-On Experience

You'll gain hands-on experience with Azure Machine Learning Studio, Azure Cognitive Services, Generative AI, NLP, Computer Vision, and more. Work on real-world projects such as building AI agents, chatbots, predictive models, and more.

Certification Preparation

Be fully prepared for 4 Microsoft Azure AI certifications:
AI-900: Azure AI Fundamentals
AI-102: Azure AI Engineer Associate
DP-100: Azure Data Scientist Associate
AZ-900: Azure Fundamentals

Job-Ready Skills

Build practical expertise aligned with real industry requirements. You'll learn to design AI solutions, implement machine learning models, work with Generative AI, and deploy scalable AI applications on Azure.

Why You Should Enroll

4 Industry Certifications

Earn globally recognized Azure certifications that prove your expertise and help you unlock high-paying AI/ML roles: AI-900: Azure AI Fundamentals AI-102: Azure AI Engineer Associate DP-100: Azure Data Scientist Associate AZ-900: Azure Fundamentals

Hands-On Experience

Gain practical experience with 60+ labs and real-world projects using Azure AI/ML tools, Azure Cognitive Services, Azure AI Foundry, and more. Work on applications like AI agents, NLP models, Generative AI, and predictive analytics.

Career Support

Receive personalized assistance with resume building, mock interviews, and job strategies designed to fast-track your career in AI/ML and cloud technologies.

Higher Earning Potential

Position yourself for career growth, transitions, and top salaries by gaining expertise in Azure AI/ML, one of the most in-demand fields in the tech industry.

Flexible Learning

Learn at your own pace with unlimited access to training materials, hands-on labs, and recordings, allowing you to fit your learning around your schedule.

Why Choose Us for the Azure Job-Oriented Program with 6 Certifications?

Practice Questions:

Access Azure AI/ML-specific questions, including full-length and topic-wise quizzes, to help you prepare for certifications and interviews. Test your knowledge and boost your confidence.

Online Courses:

Enjoy 70+ hours of structured, in-depth training. We cover everything from AI fundamentals to advanced AI/ML topics, including Azure AI services, Generative AI, NLP, Machine Learning, and Deep Learning.

Hands-on Labs:

Work on 60+ practical labs and real-world projects that simulate industry challenges. Gain valuable experience implementing Azure AI solutions, building Generative AI apps, developing NLP models, and much more.

Expert Support:

Get personalized guidance from Azure AI/ML experts. Clear your doubts, learn best practices, and refine your skills with expert feedback.

Job Aspects:

Understand the Azure AI job market, the in-demand skills employers are looking for, and how to align your learning with their needs. Prepare for interviews and boost your chances of landing your dream job in AI/ML.

On-Job Support:

Once you land your AI/ML role, continue receiving support from our experts. They’ll help you apply what you’ve learned and guide you through real-world challenges in the workplace.

Course Validity:

Enjoy 1-year unlimited access to all training materials. Learn at your own pace, and return to revise anytime until you’re fully job-ready.

Testimonials/Feedback

Join over 45,000 learners who have successfully transitioned into AI/ML roles. Hear their success stories and learn how our program has helped them achieve their career goals.

Additional Perk

By the end of the program, you’ll have the practical experience and certifications that are highly valued by employers, positioning you to excel in AI/ML interviews and on the job!

What Our Trainees Say

Trusted by thousands of satisfied trainees across multiple platforms

Insights from Our Achievers..

FAQs – Frequently Asked Questions

How long is the program?

The program lasts for approximately 2 – 3 months.

You’ll earn 4 industry-recognized certifications:

  • AI-900: Azure AI Fundamentals 
  • AI-102: Azure AI Engineer Associate
  • DP-100: Azure Data Scientist Associate 
  • AZ-900: Azure Fundamentals

Yes, beginners are welcome! The program starts with foundational AI and machine learning concepts, building up to advanced topics and hands-on projects.

You can apply for roles like AI Engineer, Machine Learning Engineer, Data Scientist, Azure AI Engineer, and NLP Engineer.

Please refer to our terms and conditions or contact support for details regarding our refund policy.

The program includes both live instructor-led sessions and recorded content for flexibility. You can learn at your own pace.

Yes, the program is designed to accommodate beginners. We cover AI fundamentals before moving on to more advanced topics.

You’ll get 24/7 access to training materials, expert guidance, doubt resolution, and job placement support throughout and after the training.

All live sessions are recorded and available to watch later.

Yes, flexible payment plans are available.

Yes, we provide study materials and exam prep.

While we cannot guarantee a job, our program significantly enhances your employability. Many learners have successfully transitioned into AI/ML roles. For example, Sreeja & Debasish Das transitioned into an Azure AI Engineer role, and Malaya Kumar Kath secured a position as a Senior Architect.

Our hands-on approach, expert support, and real-world experience equip you with the skills and confidence to stand out to potential employers.

6 Months Money Back Guarantee

When you join the K21Academy, you are fully protected by our 100% Money back guarantee.

We strive to provide the best training programs, but if you don’t get the desired results even after following every step of our learning style, you can claim your money back! 100% money-back guarantee covers the price of online training.

You have 6 Months from the date of the original purchase, to claim a refund. All you will be required to do is, show us the proof that you took action and attended sessions, completing the hands-on labs, Projects & applying to at least 50 jobs & get CV Reviewed (share proof) & you feel that the program is not worth the money you invested, you will receive a full refund.

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My 24+ Years of Experience with over 45,000+ trainees

I started my IT career in 2000 as an Oracle DBA/Apps DBA. The first few years were tough (<$100/month), with very little growth.

In 2004, I moved to the UK. After working really hard, I landed a job that paid me £2700 per month.

In February 2005, I saw a job that was £450 per day, which was nearly 4 times of my then salary.

So I looked at training from Oracle for 5 days. In November, I successfully transitioned to Oracle Security & IAM, and my career took off.

Around 2012–13, Cloud, DevOps & Cloud Automation were gaining popularity & there were many job opportunities in these fields.

So, I decided to make a change in my career path, and I transitioned from working on On-premises (Security, Infrastructure & Databases) to focusing on Cloud & DevOps.
Learning Cloud & DevOps gave me the opportunity to work with some of the world’s largest and most prestigious clients.

I then used the same roadmap with 45,000+ individuals (like you) to help them get their dream jobs.

If they can do it, you can do it too!