Azure Machine Learning course in Hyderabad
with
100% Placement Assistance
- Capstone Projects
- Industry Ready Curriculum
- Start From Foundation Level Training
Batch Details
| Trainer Name | Bharath Sri Ram,sandeep and Dinesh sir |
| Trainer Experience | 10+ Years, 20+ Years |
| Next Batch Date | 21st January 2026 (08:30 AM IST Offline)21st January 2026(08:30 AM Online) |
| Training Modes | Classroom Training (Hyderabad), Online Training |
| Course Duration | 3 Months |
| Call us at | +91 9885044555 |
| Email Us at | genaimasters@gmail.com |
| Demo Class Details | Click Here to Chat on Whatsapp |
Azure Machine Learning course in Hyderabad
Course Curriculum
- What is Machine Learning and Artificial Intelligence
- Types of Machine Learning (Supervised, Unsupervised, Reinforcement)
- Real-world ML Applications
- ML Lifecycle & Industry Use Cases
Overview of Azure AI & Cloud ML
- What is Azure Machine Learning Service
- Azure ML Architecture & Components
- Azure Machine Learning Studio Overview
- Creating Azure ML Workspace
- Compute Instances & Clusters
- Regression, Classification, Clustering Concepts
- Training vs Testing Data
- Model Evaluation Metrics
- Overfitting & Underfitting
Feature Engineering Basics
- Importing Data into Azure ML
- Data Cleaning & Transformation
- Handling Missing Data
- Data Splitting (Train/Test/Validation)
Feature Selection & Engineering
- What is AutoML
- Creating AutoML Experiments
- Algorithm Selection Automatically
- Hyperparameter Tuning
Model Comparison & Selection
- Linear Regression
- Decision Tree Regression
- Model Training Pipelines
- Evaluation & Performance Metrics
- Deploying Regression Models
- Logistic Regression
- Decision Trees & Random Forest
- Multiclass & Binary Classification
- Confusion Matrix & Accuracy Metrics
Deployment of Classification Models
- K-Means Clustering
- Unsupervised Learning Concepts
- Customer Segmentation Projects
- Evaluation Techniques
Visualization of Clusters
- Drag & Drop ML Pipelines
- Dataset Components
- Training & Inference Pipelines
- Model Deployment Using Designer
Real-Time Prediction Service
- Using Jupyter Notebooks in Azure
- Azure ML Python SDK
- Training Models with Python Scripts
- Experiment Tracking
Model Registration
- What is MLOps
- Azure ML Pipelines
- CI/CD for Machine Learning
- Model Versioning
Automation & Scheduling
- Real-time Endpoints
- Batch Inference
- Azure Container Instances (ACI)
- Azure Kubernetes Service (AKS)
Monitoring & Logging Models
- Role-Based Access Control (RBAC)
- Data Privacy & Compliance
- Model Explainability
- Bias & Fairness in AI
Governance & Auditing
- Hyperparameter Tuning
- Distributed Training
- GPU & Compute Scaling
- Performance Optimization
Data Drift Monitoring
- Azure OpenAI Integration
- Model Catalog & Prompt Flow
- Building AI Apps with Azure ML
- Deployment of AI Models
- Enterprise AI Solutions
- Sales Prediction Project
- Customer Churn Prediction
- Image Classification Project
- NLP Text Analysis Project
End-to-End Industry Capstone Project
- Azure Data Factory Overview
- Connecting Azure Blob, SQL, Data Lake
- Data Pipelines for ML
- ETL for Machine Learning
Data Orchestration in Cloud
- Introduction to Azure Databricks
- Spark for ML Workflows
- Data Processing with Notebooks
- MLlib Basics
- Integrating Databricks with Azure ML
- Big Data Concepts
- Batch vs Streaming Data
- Azure Synapse Analytics
- Data Warehousing for ML
- Real-Time Analytics Pipelines
- Neural Networks Basics
- TensorFlow & PyTorch in Azure
- Deep Learning Training in Azure
- GPU Training Models
- Image & NLP Deep Learning Use Cases
- Image Classification Models
- Object Detection Basics
- Azure Vision Services
- Custom Vision Models
- Real-Time Vision Applications
- Text Classification
- Sentiment Analysis
- Azure Cognitive Language Services
- Chatbot NLP Models
- Text Analytics Projects
- Azure Cognitive Services Overview
- Vision, Speech, Language APIs
- AI Services with Azure ML
- Building AI-Powered Applications
Enterprise AI Integration
- Model Version Control
- Model Registry
- Retraining Strategies
- Model Lifecycle Governance
Enterprise ML Governance
- Azure Monitor for ML
- Logging Experiments
- Error Handling
- Data Drift Detection
- Model Performance Tracking
- Designing ML Cloud Architecture
- Azure Storage & Compute Architecture
- Cost Optimization
- High Availability & Scalability
Enterprise Architecture Patterns
- Azure Security Best Practices
- Identity & Access Management
- Compliance Standards (GDPR, ISO)
- Secure ML Pipelines
Data Governance Policies
- Azure Pricing for ML
- Compute Cost Optimization
- Storage Cost Strategies
- Budget Monitoring
Enterprise Cost Planning
- Web Apps with ML APIs
- Power Apps Integration
- AI in Business Applications
- Low-Code AI Apps
- Enterprise Use Cases
- Azure ML Interview Questions
- Real-Time Industry Scenarios
- Resume & Portfolio Guidance
- GitHub Project Portfolio
Placement Preparation & Mock Interviews
Trainer Details - Azure Mechin Learning Course in Hyderabad
Ms. Madhumathi
Principal Data Scientist & Generative AI Strategist
10+ Years of Experience
About the Tutor
As a lead trainer and industry mentor, she focuses on empowering learners to design, train, and deploy real-world Machine Learning models using Azure Machine Learning Studio, Python, and Azure cloud infrastructure. Her training methodology combines strong conceptual clarity with hands-on, enterprise-level projects.
She brings practical expertise in tools and technologies such as Python, Azure ML Studio, Azure Data Factory, REST APIs, and MLOps pipelines, helping learners confidently apply Machine Learning across business, marketing, healthcare, and technology domains. Her approachable teaching style, real-time demos, and project-driven learning ensure students become job-ready and industry-confident.
Mr. Dinesh
Azure Machine Learning AI Authority & Principal Data Scientist
20+ years of Experience
About the Tutor
Our tutor is an Azure Machine Learning Specialist and Lead Data Scientist with strong expertise in Machine Learning, Deep Learning, Data Science, and Artificial Intelligence, supported by advanced Python programming and analytical skills.
As a dedicated mentor, she emphasizes career development, analytical thinking, and real-world ML project experience, preparing learners for successful careers in the global AI and Data Science industry.
Why Choose us for Azure Azure Machine Learning course in hyderabad
Expert Faculty
Azurea Ai Masters is led by a team of experienced industry experts in Generative AI. Their extensive knowledge and hands-on experience ensure high-quality, practical training.
Complete Curriculum
Our Azure Machine Learning program covers everything from cloud fundamentals and ML basics to advanced Azure AI services, model deployment, MLOps, and enterprise use cases—giving you complete end-to-end knowledge.
Hands-On Learning
Students get hands-on experience with Azure Machine Learning Studio, Python, Data Science workflows, AutoML, and real datasets. Practical labs ensure you learn by building real AI models.
Industry-Relevant Projects
You will work on real-world Azure ML projects such as predictive analytics, NLP, computer vision, recommendation systems, and cloud AI deployments—aligned with current industry demands.
State-of-the-Art Facilities
The institute is оснащed with advanced technology and cutting-edge software required for Generative AI training, ensuring students access the latest tools and resources.
Personalized Support
One-on-one guidance to address learning gaps and align training with career goals.
Career Assistance
Our team helps you with resume building, LinkedIn optimization, mock interviews, and job placement assistance to ensure you are industry-ready.
Networking Opportunities
Students connect with Azure professionals, AI experts, industry mentors, and alumni communities, opening doors to internships, jobs, and collaborations.
Flexible Learning Options
Online, classroom, and hybrid training options for students and working professionals.
Strong Reputation
Recognized as a leading Azure Machine Learning training institute in Hyderabad.
Modes - Azure Machine Learning course in hyderabad
Classroom Training
- Interactive Face-to-Face Teaching
- Industry Expert Trainers
- Instant Feedback
- Collaborative Tasks
- Hands-on Industry Projects
- Group Discussions
- Covers Advanced Topics
Online Training
- Virtual Learning Sessions
- Daily Session Recordings
- Instructor Support
- Interactive Webinars
- Digital Learning Modules
- Online Practical Labs
- Flexible Learning Schedules
Corporate Training
- Customized Training Programs
- Daily Recordings
- Interactive Team Development
- Expert Instruction
- Industry-Relevant Content
- Performance Monitoring
- On-Site Workshops
What is Azure Machine Learning What is Azure Machine Learning
- Azure Machine Learning is Microsoft’s cloud-based platform for building, training, and deploying Machine Learning models.
- Key Features of Azure Machine Learning:
- Enables organizations to build, deploy, and manage ML models at scale
- Provides secure, enterprise-ready ML infrastructure
- Supports automated Machine Learning and custom model development
- Handles structured and unstructured data
- Enables predictive analytics, recommendation systems, and AI automation
- Integrates with Python, Jupyter, TensorFlow, PyTorch, and Scikit-learn
- Supports MLOps pipelines for model lifecycle management
- Enables real-time model deployment through APIs and cloud endpoints
- Provides data preparation, model training, monitoring, and governance tools
If you want to learn more about Generative AI Syllabus
Tools Covered as part of Azure Machine Learning Course
In Generative AI training, participants usually learn to use different tools and software that are important for building and handling generative AI models. These tools include
An open-source machine learning framework widely used for building and training neural networks.
Hugging Face Transformers
A library that provides pre-trained models and tools for natural language processing and other generative tasks.
OpenAI GPT
Jupyter Notebooks
NVIDIA CUDA
Google Colab
Docker
Skills Develop After Azure Machine Learning Course In Hyderabad
- Gain expertise in designing, building, and deploying machine learning models using Microsoft Azure Machine Learning for prediction, automation, analytics, and intelligent business systems.
- Learn to create high-accuracy predictive models for business forecasting, customer analytics, fraud detection, and decision support systems using cloud-based ML workflows.
- Develop a deep understanding of machine learning algorithms, neural networks, supervised and unsupervised learning, model training, and optimization techniques.
- Master integration of Azure ML with Azure Data Factory, Azure Synapse, Azure Databricks, Power BI, and Azure OpenAI, enabling end-to-end AI solutions on the cloud.
- Gain skills in Azure AutoML to build AI models without coding, making AI development faster and accessible for beginners and professionals.
- Work on real-time industry projects and case studies to solve practical problems such as predictive analytics, NLP, image recognition, and recommendation systems.
- Learn to evaluate, tune, and optimize machine learning models to improve accuracy, performance, and scalability using Azure ML pipelines.
- Understand ethical AI principles, data privacy, fairness, and compliance standards for enterprise-level AI deployment.
Job Opportunities on Generative AI
Azure Machine Learning skills are highly in demand across industries like IT, banking, healthcare, real estate, e-commerce, and government sectors. After completing Azure ML training, you can apply for the following roles:
- Azure Machine Learning Engineer
- Designs, builds, and deploys machine learning models on Microsoft Azure. Works with cloud data pipelines, AI models, and enterprise ML solutions.
- AI / ML Research Engineer
- Conducts research on machine learning algorithms, deep learning models, and cloud AI innovations to improve predictive systems and intelligent applications.
- Data Scientist
- Analyzes large datasets, builds predictive models, and delivers insights using Azure ML, Python, and data analytics tools to support business decisions.
- Azure AI Developer
- Develops AI-driven applications, APIs, and cloud-based AI services using Azure Machine Learning, Azure AI Services, and Python programming.
- Computer Vision Engineer
- Works on image recognition, video analysis, and vision-based AI systems using Azure Cognitive Services and deep learning models.
- NLP Engineer
- Builds language-based AI systems such as chatbots, text analytics tools, and conversational AI using Azure ML and NLP frameworks.
- Cloud AI Product Manager
- Manages AI product development, cloud AI solutions, and machine learning deployments, ensuring business requirements are met.
- Azure AI Consultant
- Advises organizations on implementing Azure AI and Machine Learning solutions to automate processes and improve business performance.
- Responsible AI & Compliance Specialist
- Ensures AI models meet ethical standards, data privacy regulations, and enterprise compliance policies.
Azure Mechine Learning Salaries in Hyderabad – 2026 (Expected)
Azure Machine Learning and Cloud AI skills are rapidly growing in Hyderabad, with strong demand from IT services companies, product-based firms, startups, and enterprise organizations.
By 2026, professionals with skills in Python, Machine Learning, Deep Learning, Azure AI, and MLOps will earn high salaries in India.
Job Role | Experience Level | Skills Required | Expected Salary (2026) | Top Hiring Companies in Hyderabad |
Azure Machine Learning Engineer | 0–3 years | Python, ML Algorithms, Azure ML Studio | ₹7–16 LPA | TCS, Infosys, Wipro, Tech Mahindra |
Machine Learning Engineer | 1–5 years | ML Models, TensorFlow, PyTorch, Python | ₹10–22 LPA | Microsoft, Accenture, Deloitte |
Azure AI Developer | 1–6 years | Azure AI Services, ML APIs, Data Science | ₹12–25 LPA | Product Companies, SaaS Firms |
Data Scientist (Azure ML) | 2–7 years | Statistics, ML, Deep Learning, Python | ₹12–30 LPA | BFSI, Healthcare, Enterprise Companies |
MLOps Engineer | 2–7 years | CI/CD, Docker, Kubernetes, Azure DevOps | ₹12–26 LPA | Cloud Companies, AI Platforms |
Computer Vision Engineer | 1–6 years | Deep Learning, Image Processing, Azure Vision | ₹10–24 LPA | Product Companies, Research Firms |
NLP Engineer | 1–6 years | NLP, Transformers, Azure Language Services | ₹10–25 LPA | SaaS Companies, AI Startups |
Cloud AI Product Manager | 4–12 years | AI Project Management, Product Strategy | ₹22–55 LPA | Product-Based Companies |
Azure AI Consultant | 5+ years | AI Strategy, Cloud Integration, Client Solutions | ₹28–65 LPA | Big 4 Consulting Firms, IT Services |
AI Research Engineer | 3–10 years | Deep Learning Research, ML Models, AI Papers | ₹18–45 LPA | Research Labs, MNCs, Universities |
Why Azure Machine Learning Salaries Are Increasing in Hyderabad
More companies are adopting AI automation and AI-powered products to improve efficiency, reduce costs, and increase productivity.
High demand for LLM developers and Prompt Engineers as businesses integrate ChatGPT, Copilot, and enterprise AI solutions.
Hyderabad is emerging as a major AI and cloud technology hub with strong investments in AI research and development.
Global tech companies are opening AI research labs and innovation centers in Hyderabad to build next-generation AI solutions.
Skilled Generative AI and Azure ML professionals are limited, which is driving higher salaries and rapid career growth opportunities.
Companies That Hire
Generative AI Placement Program
Azure Machine Learning Masters Institute provides a comprehensive placement assistance program to help students secure high-paying roles in AI and cloud-based machine learning. The program is designed to prepare learners for real-world job opportunities in top tech companies.
Students receive personalized career guidance, resume-building support, and mock interview training to confidently present their Azure ML skills to recruiters. The institute also helps candidates showcase real-world projects, technical expertise, and industry-ready knowledge to potential employers.
Through industry connections, hiring partnerships, and recruitment drives, students get access to job openings, networking opportunities, and career mentorship, ensuring a smooth transition from learning to employment.
Intensive 3-Month Industry-Focused Curriculum
Enroll in a structured and hands-on Azure Machine Learning training program with practical assignments, real-world tasks, and guided labs to build deep technical expertise.
End-to-End Real-Time Project Implementation
Work on complete Azure ML projects, including data pipelines, model training, deployment, and monitoring—just like in real industry environments.
Advanced Capstone Projects
Develop multiple capstone projects using Azure AI, Machine Learning Studio, and cloud-based ML workflows to strengthen your portfolio and demonstrate job-ready skills.
Practical Industry Work Experience
Gain hands-on exposure to enterprise-level AI and ML scenarios, preparing you for real corporate challenges and production environments.
Interview & Career Preparation
Get expert mentoring for technical interviews, coding rounds, Azure ML concepts, and real-time scenario-based questions to boost your job confidence.
Simulated Corporate Work Environment
Train in a simulated enterprise environment with team-based tasks, deadlines, and collaborative projects to experience real-world AI development workflows.
Difference between Traditional Training and Generative AI Masters
- Traditional Training
- Generative AI Masters Training
Theory-Focused Learning
- Mostly basic concepts with classroom theory and limited real-world exposure.
Industry-Oriented Practical Training
- Hands-on labs, cloud projects, and real-time Azure ML use cases aligned with industry standards.
Limited Practical Exposure
- Minimal real-world projects and outdated training methods.
100% placement assistance
- Resume building, mock interviews, interview scheduling, and career guidance support.
No Job Support
- Training ends after course completion, and students must search for jobs on their own.
Industry Ready Curriculum
- Designed by AI and cloud experts with advanced Azure ML, Data Science, and MLOps topics.
Basic Curriculum
- General syllabus with outdated or limited topics.
Flexible Payment Options
- Small initial fee with easy installment plans for students and professionals.
High Upfront Course Fees
- Large payment required before training starts.
Top partnered companies
- Strong partnerships with IT services, startups, and product companies.
Very Limited Corporate Tie-Ups
- Few hiring partnerships and limited placement opportunities.
Systematic training program
- Structured modules, assignments, projects, mentorship, and online + offline support.
Azure AI Masters Course In Hyderabad
5000+ jobs Opening for Azure Machine Learning
Pre-requisites to attend Azure Machine Learning Course Online
- A basic understanding of Python programming is helpful for building machine learning models, writing scripts, and working with Azure ML notebooks.
- Basic Mathematics Knowledge Understanding linear algebra and calculus concepts such as vectors, matrices, gradients, and optimization is useful for learning how ML models work internally.
- Data Handling & Analysis Skills Prior experience with data manipulation tools like Pandas, NumPy, Excel, or SQL will help you work with real-world datasets in Azure ML projects.
Generative AI Market Trends
- Azure Machine Learning (Azure ML) is rapidly growing as enterprises move toward cloud-based AI, automation, and data-driven decision-making. The market is expanding across multiple industries and creating strong demand for skilled professionals.
- Rapid Adoption of Cloud AI & Machine Learning
- Organizations are increasingly using Azure ML to build predictive models, automate workflows, and enhance business intelligence, making cloud-based AI a core digital transformation strategy.
- Enterprise Use Across Multiple Industries
- Azure Machine Learning is widely adopted in:
- Banking & Finance
- Healthcare
- E-commerce
- Manufacturing
- Real Estate
- Government & Smart Cities
- Companies use Azure ML for forecasting, fraud detection, recommendation systems, and automation.
- Rising Demand in Healthcare & Life Sciences
- Healthcare organizations use Azure ML for disease prediction, medical imaging, drug research, and clinical data analysis, increasing AI adoption in the medical sector.
- Heavy Investment by Enterprises
- Global companies are investing heavily in Azure AI platforms, cloud data pipelines, and machine learning automation to improve productivity, reduce costs, and enhance business operations.
- User-Friendly Cloud AI Platforms
- Microsoft Azure ML is becoming more accessible with no-code/low-code tools, drag-and-drop interfaces, and AutoML features, allowing beginners and professionals to build AI models easily.
- Ethical AI, data privacy, and governance are gaining importance. Companies are implementing Responsible AI frameworks, compliance standards, and secure cloud AI practices.
Our Great Achievements
Generative AI Learners Testimonials
Highlights Of Generative AI Course
- The Azure ML course is designed to give a complete understanding of machine learning, cloud AI, and enterprise data science workflows.
- Students learn to build, train, and deploy machine learning models on Azure Cloud for real-world applications like prediction, automation, and analytics.
- Real-time industry projects and case studies help students gain practical experience and job-ready skills.
- Training is delivered by certified Azure professionals and AI industry experts with real-world enterprise experience.
- Students get access to Azure ML Studio, cloud labs, datasets, notebooks, and enterprise AI tools provided by AzureAiMasters.
- Students get access to Azure ML Studio, cloud labs, datasets, notebooks, and enterprise AI tools provided by AzureAiMasters.
Generative AI Masters Course Outline
01
Azure AIMasters Machine Learning & Deep Learning Fundamentals and Students learn core concepts such as:
02
Training covers Azure Machine Learning Studio, Azure AI services, Python notebooks, datasets, and ML pipelines, helping students understand the Azure AI ecosystem.
03
Explore real-world case studies from banking, healthcare, retail, real estate, and manufacturing to understand how Azure ML is used in production environments.
04
Learn AI ethics, data privacy, fairness, bias mitigation, and compliance best practices for enterprise AI deployment.
05
Students work on industry-based projects such as Predictive analytics and Customer behavior predictionand Fraud detection Recommendation systems
06
Explore real-world case studies from banking, healthcare, retail, real estate, and manufacturing to understand how Azure ML is used in production environments.
07
Learn AI ethics, data privacy, fairness, bias mitigation, and compliance best practices for enterprise AI deployment.
08
The course concludes with:Model deployment on Azure
And MLOps pipelines (CI/CD, monitoring)and Resume building & interview preparationand Placement and career support
Certification
Top Certifications Related to Azure Machine Learning & AI
Microsoft Azure AI Engineer Associate (AI-102)
Covers Azure Machine Learning, Cognitive Services, AI model deployment, and real-world cloud AI applications.
Microsoft Azure Data Scientist Associate (DP-100)
Focuses on building, training, and deploying machine learning models using Azure Machine Learning Studio and Python.
Google Cloud Professional Data Engineer
Includes machine learning and AI concepts relevant to cloud-based ML solutions and enterprise data engineering.
Deep Learning Specialization – Coursera (Andrew Ng)
Covers neural networks, deep learning, and AI fundamentals useful for Azure ML and generative AI workflows.
Machine Learning and AI Foundations – Microsoft
Provides foundational knowledge of AI, machine learning concepts, and cloud-based AI applications.
Deep Learning Specialization – Udacity
Focuses on deep learning architectures and model development, helpful for building ML models on Azure.
NVIDIA Deep Learning Institute Certifications
Offers training and certifications in deep learning, GPU computing, and AI model optimization.
If you want to learn more about Azure Ai Masters Certification
Faqs
Azure Machine Learning is a Microsoft cloud service used to build, train, deploy, and manage machine learning models at scale.
Students, fresh graduates, IT professionals, developers, data analysts, and anyone interested in AI and Data Science can learn Azure ML.
Basic Python knowledge is recommended, but beginners can also start with foundation classes.
Basic knowledge of Python, statistics, machine learning concepts, and data handling is helpful but not mandatory.
Azure ML is beginner-friendly with AutoML and no-code tools, but advanced topics require practice and learning.
You can become:
Azure ML Engineer
Data Scientist
AI Engineer
MLOps Engineer
Cloud AI Developer
Typically, the course duration is 2 to 4 months, depending on the curriculum and training mode.
Yes, the course includes industry-based real-time projects and case studies.
Yes, we provide 100% placement assistance, resume building, and interview preparation.
Yes, students receive course completion certification and guidance for Microsoft Azure certifications.
Freshers can earn ₹6 LPA – ₹12 LPA, and experienced professionals can earn ₹20 LPA – ₹60+ LPA.
Yes, Hyderabad is a major hub for cloud, AI, and data science jobs, with high demand for Azure ML professionals.
You will learn:
Azure ML Studio
Python
Jupyter Notebook
TensorFlow / PyTorch
Azure Data Factory
MLOps Tools
Banking, Healthcare, E-commerce, Real Estate, Manufacturing, IT, and Government sectors use Azure ML.
Yes, Azure ML is a great career option for freshers with strong growth and salary potential.
Yes, the course includes MLOps, model deployment, monitoring, and CI/CD pipelines.
Azure ML focuses on machine learning models and analytics, while Generative AI focuses on content generation like text, images, and audio.
You can contact us via WhatsApp, call, or enroll through our website for a free demo class
