AI ML Course In Hyderabad
with
100% Placement Assistance
- Capstone Projects
- Industry Ready Curriculum
- Start From Foundation Level Training
AI ML Course In Hyderabad
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 |
AI ML Course In Hyderabad
Course Curriculum
- What is AI, ML, and Deep Learning
- History and evolution of AI
- AI applications in real life
- AI lifecycle
Career roles in AI
- Python basics for AI
- NumPy and Pandas
- Data structures and functions
- Data visualization with Matplotlib
Python best practices
- Mean, median, variance
- Probability basics
- Linear algebra fundamentals
- Matrices and vectors
Statistical distributions
- Data cleaning
- Handling missing values
- Feature scaling and normalization
- Encoding categorical data
Data splitting (train/test)
- Regression vs classification
- Model training process
- Evaluation metrics
- Overfitting and underfitting
- Cross-validation
- Simple and multiple regression
- Cost function
- Gradient descent
- Model evaluation
Real-world regression examples
- Binary and multiclass classification
- Sigmoid function
- Decision boundaries
- Evaluation metrics
Practical projects
- Tree structure
- Splitting criteria
- Pruning techniques
- Advantages and limitations
Real-world use cases
- Ensemble learning concept
- Bagging technique
- Random forest algorithm
- Hyperparameter tuning
Practical implementation
- Margin and hyperplane
- Kernel functions
- Classification and regression
- Tuning SVM models
Industry use cases
- Clustering vs dimensionality reduction
- K-means clustering
- Hierarchical clustering
- PCA (Principal Component Analysis)
Use cases
- Algorithm working
- Choosing K value
- Elbow method
- Real-world clustering projects
Visualization techniques
- Dimensionality reduction
- Eigenvectors and eigenvalues
- PCA workflow
- Visualization
Practical examples
- Artificial neurons
- Perceptron model
- Activation functions
- Forward and backward propagation
Neural network architecture
- Deep neural networks
- CNN and RNN overview
- Deep learning frameworks
- Training deep models
Use cases
- Text preprocessing
- Tokenization and stemming
- Bag of words and TF-IDF
- Sentiment analysis
Chatbot basics
- Image processing concepts
- Image classification
- Object detection
- CNN basics
Vision applications
- ML pipelines
- Model building
- Hyperparameter tuning
- Model evaluation
Practical projects
- TensorFlow basics
- Keras models
- Neural network training
- Model optimization
Deep learning projects
- Model serialization (Pickle, Joblib)
- REST API deployment
- Flask/FastAPI deployment
- Cloud deployment overview
Real-time inference
- DevOps vs DataOps vs MLOps
- ML lifecycle in production
- CI/CD for ML
- Model versioning
Enterprise ML workflows
- Cloud ML platforms
- Azure Machine Learning basics
- Cloud compute and storage
- Training models on cloud
Deployment pipelines
- Data pipelines
- ETL process
- Data lakes and warehouses
- Streaming data
Big data basics
- Model drift detection
- Performance monitoring
- Logging and analytics
- Retraining strategies
Production challenges
- Bias and fairness
- Data privacy
- Ethical AI frameworks
- Regulations and compliance
Responsible AI design
- Healthcare AI
- Finance AI
- Real estate AI
- Marketing AI
Education AI
- Problem statement selection
- Data collection and preprocessing
- Model training and evaluation
- Deployment
Final project presentation
- Scikit-learn
- TensorFlow / PyTorch
- Jupyter Notebook
- Git & GitHub
ML project workflow tools
- AI & ML interview questions
- Coding interview practice
- Case study questions
- Resume building
Portfolio projects
- Generative AI
- Agentic AI
- AutoML
- AI careers roadmap
Industry trends and salaries
Trainer Details - AI ML Course In Hyderabad
Ms. Madhumathi
Principal Data Scientist & Generative AI Strategist
10+ Years of Experience
About the Tutor
Ms. Madhumathi is a highly experienced Data Scientist with over a decade of hands-on expertise in Artificial Intelligence and Machine Learning. She has a strong background in building data-driven solutions and transforming raw data into actionable insights.
As a senior trainer and mentor, she is deeply committed to shaping students’ careers by combining conceptual clarity with practical exposure. Her sessions emphasize real-time use cases, industry datasets, and hands-on problem-solving approaches.
Ms. Madhumathi also introduces learners to essential tools and technologies such as Python, TensorFlow, Scikit-learn, SQL, and cloud-based ML workflows, ensuring students gain confidence in applying AI and ML solutions across domains like business analytics, marketing intelligence, and technology-driven decision systems.
Her interactive teaching style, combined with practical demonstrations and project-based learning, helps students develop strong technical skills and the confidence to work on real-world AI and Machine Learning applications.
Mr. Dinesh
Generative AI Authority & Principal Data Scientist
20+ years of Experience
About the Tutor
Mr. Dinesh is a seasoned AI and Machine Learning professional with more than two decades of experience in data science, advanced analytics, and intelligent systems development. His expertise spans Machine Learning, Deep Learning, NLP, Python, R, and advanced statistical modeling.
He has a unique ability to simplify complex AI concepts, making them accessible to learners from both technical and non-technical backgrounds. His training methodology focuses on step-by-step explanations, practical implementation, and real-world case studies that bridge theory with application.
Mr. Dinesh has extensive international exposure, having led and managed large-scale projects across healthcare, medical analytics, and research domains in the US, UK, Australia, and Canada. He brings strong experience in image processing, medical data analysis, and disease prediction models using AI and Machine Learning techniques.
He actively guides students in working with industry-standard frameworks and tools such as TensorFlow, PyTorch, Scikit-learn, and enterprise-level ML pipelines, enabling them to design, build, and deploy robust AI solutions.
Why Choose us for AI ML Course In Hyderabad
Expert Faculty
Azure AI Masters Our institute is led by highly experienced AI and Machine Learning professionals with extensive industry exposure. Their real-world knowledge ensures students receive practical, relevant, and up-to-date training.
Complete Curriculum
The course curriculum is carefully designed to cover core AI and Machine Learning concepts, from foundational principles to advanced algorithms and real-time applications, providing a complete learning journey.
Hands-On Learning
Students participate in practical labs and exercises that reinforce theoretical concepts through implementation, helping them build strong problem-solving and model-building skills.
Industry-Relevant Projects
Learners work on real-world projects aligned with current industry requirements, enabling them to understand real-time challenges and apply AI/ML techniques effectively.
State-of-the-Art Facilities
The training environment is equipped with modern systems, tools, and software required for AI and Machine Learning development, ensuring students gain exposure to industry-grade resources.
Personalized Support
We provide one-on-one guidance and mentorship to support individual learning goals, ensuring students receive the attention and direction needed to succeed.
Career Assistance
Our program includes resume preparation, interview coaching, and job assistance to help students confidently enter the AI and Machine Learning job market.
Networking Opportunities
Students gain access to a strong professional network of mentors, alumni, and industry experts, opening doors to collaboration and career opportunities.
Flexible Learning Options
We offer classroom training, online sessions, and hybrid learning options to suit different schedules and learning preferences.
Strong Reputation
With consistently positive student feedback and strong industry recognition, our institute has established itself as a reliable destination for AI and Machine Learning training in Hyderabad.
Modes - AI ML 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 AI ML Course In Hyderabad
Artificial Intelligence (AI) is a branch of computer science that enables machines to simulate human intelligence, such as learning, reasoning, and decision-making.
Machine Learning (ML) is a core subset of AI that allows systems to learn from data and improve their performance over time without being explicitly programmed for every task.
AI and Machine Learning rely on advanced algorithms, statistical models, and neural networks to analyze data, identify patterns, and make accurate predictions or classifications.
If you want to learn more about AI AND ML SYLLABUS
Tools Covered as part OF AI ML Course In Hyderabad
In AI AND ML , participants usually learn to use different tools and software that are important for building and handling AI AND ML models. These tools include
An open-source machine learning framework widely used for building and training neural networks.
KNIME (Konstanz Information Miner) is an open-source data analytics, reporting, and integration platform.
It allows you to build data workflows using a drag-and-drop interface
Hugging Face Transformers
OpenAI GPT
Jupyter Notebooks
OPENAI
OpenAI is an artificial intelligence research and product company focused on building advanced, safe, and useful AI systems.
SPARK ML
A machine learning library built into Apache Spark for working with very large datasets.
SCIKIT LEARN
Scikit-learn is the go-to ML toolkit for Python learners—simple, clean, and powerful.
Skills Develop After AI ML Course In Hyderabad
- Ability to design, build, and deploy advanced AI and Machine Learning models for a wide range of applications, including automation, data-driven decision systems, predictive analytics, and intelligent business solutions.
- Proficiency in developing high-quality analytical outputs such as predictions, classifications, recommendations, and pattern detection using Machine Learning techniques, ensuring accuracy, reliability, and real-world relevance across multiple use cases.
- Strong understanding of core Machine Learning and Deep Learning fundamentals, including neural networks, model training workflows, loss functions, optimization methods, and performance evaluation techniques that form the backbone of intelligent systems.
- Knowledge of various Machine Learning and Deep Learning model architectures, such as regression models, decision trees, ensemble methods, convolutional neural networks (CNNs), and recurrent neural networks (RNNs), along with their practical industry applications.
- Hands-on experience in applying AI and Machine Learning solutions to real-world projects and case studies, demonstrating the ability to solve practical problems, improve automation, and develop data-driven applications used in real business environments.
- Skills in model evaluation, tuning, and optimization, including hyperparameter tuning, performance improvement, accuracy enhancement, and handling overfitting or underfitting issues.
- Awareness of ethical AI practices, data privacy principles, responsible model usage, bias mitigation, and best practices for deploying Machine Learning solutions in real-world scenarios.
- Competence in using industry-standard AI and Machine Learning tools and software, such as Python-based libraries, ML frameworks, data analysis platforms, and deployment tools, to efficiently build, manage, and maintain AI-driven projects.
Job Opportunities on AI ML Course In Hyderabad
Career opportunities in Artificial Intelligence and Machine Learning are rapidly expanding as organizations across industries adopt intelligent, data-driven systems. Professionals with AI and ML expertise are in high demand for both technical and strategic roles.
Key Career Roles in AI & Machine Learning
- AI Research Scientist – Focuses on researching and developing new AI and Machine Learning algorithms, improving existing models, and advancing intelligent system capabilities.
- Machine Learning Engineer – Designs, builds, and deploys Machine Learning models that power predictive systems, automation tools, and intelligent applications.
- Data Scientist – Works with large and complex datasets to extract insights, build ML models, and support data-driven decision-making processes.
- AI Application Developer – Develops and integrates AI-powered applications using Machine Learning models for analytics, automation, and intelligent workflows.
- Computer Vision Engineer – Specializes in image and video analysis, object detection, pattern recognition, and visual data processing using AI and Deep Learning techniques.
- Natural Language Processing (NLP) Engineer – Builds systems that analyze, understand, and process human language for applications such as text analytics, chat systems, and language classification.
- AI Product Manager – Manages the planning, development, and deployment of AI-driven products while aligning technical solutions with business goals.
- AI Consultant – Advises organizations on adopting AI and Machine Learning solutions to improve operations, optimize performance, and solve complex business challenges.
- AI Trainer / Instructor – Provides professional training and education in AI and Machine Learning to students, teams, and corporate organizations.
AI ML Course In Hyderabad Salaries in Hyderabad – 2026 (Expected)
Hyderabad is emerging as a major hub for AI and Machine Learning, with strong demand from IT services, startups, research centers, and product-based companies. By 2026, the need for skilled professionals in Machine Learning, Deep Learning, NLP, AI engineering, and MLOps is expected to grow significantly.
| Job Role | Experience Level | Key Skills Required | Expected Salary (2026) | Who Hires in Hyderabad |
|---|---|---|---|---|
| AI Engineer | 0–3 years | Python, Machine Learning, NLP, AI frameworks | ₹8–18 LPA | TCS, Infosys, Wipro, Amazon, Google |
| Machine Learning Engineer | 1–5 years | ML algorithms, Python, TensorFlow, PyTorch | ₹10–22 LPA | Microsoft, Accenture, Deloitte |
| AI Application Developer | 1–6 years | ML models, APIs, data pipelines | ₹12–28 LPA | Startups, Product-based companies |
| NLP Engineer | 1–6 years | NLP models, text processing, embeddings | ₹10–25 LPA | SaaS firms, Product companies |
| Data Scientist (AI & ML) | 2–7 years | Statistics, ML, Deep Learning | ₹12–30 LPA | BFSI, Healthcare, Enterprise firms |
| AI Research Scientist | 3–10 years | Research, Deep Learning, model experimentation | ₹20–50 LPA | Research labs, Universities, MNCs |
| AI Product Manager | 4–12 years | AI project management, product strategy | ₹25–60 LPA | Product-based organizations |
| MLOps Engineer | 2–7 years | ML deployment, CI/CD, Cloud, Docker, Kubernetes | ₹12–26 LPA | Cloud providers, AI platforms |
| AI Consultant | 5+ years | AI strategy, enterprise solutions | ₹30–70 LPA | Big 4 firms, IT consulting companies |
Why AI AND ML Salaries Are Increasing in Hyderabad
- Rapid adoption of AI-driven automation and intelligent systems across industries
- High demand for Machine Learning Engineers, NLP specialists, and AI engineers
- Hyderabad’s growth as a center for AI research, innovation, and technology hubs
- Expansion of global companies establishing AI and analytics centers in the city
Companies That Hire
AI ML Course In HyderabadPlacement Program
This program focuses on preparing learners not only with technical expertise but also with the career readiness required to succeed in competitive hiring environments.
The placement support includes personalized career counseling, professional resume creation, and structured interview preparation. These services help candidates present their technical skills, project experience, and problem-solving abilities effectively to potential employers.
Students also gain access to a strong industry network and curated job opportunities through collaborations with technology companies, consulting firms, and product-based organizations. The institute regularly organizes job fairs, recruitment drives, and professional networking sessions, allowing learners to interact directly with recruiters and industry experts.
AI & Machine Learning Placement Program Highlights
Intensive 3-Month Curriculum
Participate in a structured, hands-on training program featuring assignments, tasks, and guided practice designed to build strong expertise in AI and Machine Learning concepts.
End-to-End Project Implementation
Gain real-world exposure by working on complete AI and ML projects, following industry-standard workflows from data preparation to model deployment.
Capstone Projects
Complete multiple capstone projects that strengthen your practical skills and demonstrate your ability to solve real business problems using AI and Machine Learning.
Practical Industry Experience
Develop hands-on experience that prepares you for real workplace challenges, including data handling, model evaluation, and solution optimization.
Interview Readiness Training
Receive expert-led interview preparation covering technical questions, problem-solving scenarios, case studies, and HR discussions.
Simulated Professional Environment
Train in a work-like environment that mirrors real industry conditions, helping you adapt quickly to professional roles and expectations.
Difference between Traditional Training and Azure AI Masters
- Traditional Training
- Azure AI Masters Training
just basics with only theory based training
- Hardly any practical Exposure with industry requirements.
Advanced practical training
- You get practical knowledge of the subject with hands-on experience as per industry requirements
Zero Job assurance
- You only receive training, after that it's up to you to find Job.
100% placement assistance
- At Generative AI Training in Hyderabad, we provide full support to help you find work, from scheduling interviews to boosting your employability.
Basic curriculum
- You are trained with generalized basic concepts.
Industry Ready Curriculum
- We follow a curated and industry demanding curriculum with advanced topics designed by the industry experts.
Huge upfront course fee
- You are charged very high course fees for training and course materials alone.
Flexible Payment Options
- We offer a small initial training fee, with the remainder payable in term installments.
Very Limited corporate tie ups
- You miss out on good hiring opportunities owing to the lack of industrial ties.
Top partnered companies
- Start your career by getting hired by the top companies in the industry. Career Development Oriented program:
Unstructured training programme
- The entire course is taught in a matter of weeks, and it is done so quickly.
Systematic training program
- We offer an extensive 3 month training program with online & offline assistance.
AI ML Course In Hyderabad
5000+ jobs Opening for AI ML
Pre-requisites to attend AI ML Course In Hyderabad
- A basic understanding of programming, especially Python, is required to develop, train, and implement Machine Learning models effectively.
- Familiarity with fundamental Machine Learning concepts and basic statistics will help learners grasp advanced AI algorithms and model behavior more easily.
- Knowledge of linear algebra and calculus is helpful for understanding the mathematical foundations behind Machine Learning algorithms, neural networks, and optimization techniques.
- Prior experience with data handling, data preprocessing, and data analysis tools will support efficient work with real-world datasets used in AI and Machine Learning projects.
AI ML Course In Hyderabad Market Trends
- Artificial Intelligence and Machine Learning are experiencing rapid growth due to their ability to analyze data, automate processes, and deliver intelligent insights across industries.
- AI and ML technologies are increasingly adopted in sectors such as entertainment, design, marketing, finance, and operations to enhance personalization, forecasting, and decision-making.
- Continuous advancements in Machine Learning algorithms, Deep Learning architectures, and data processing techniques are driving innovation and expanding AI capabilities.
- There is growing adoption of AI and ML in healthcare, particularly for medical data analysis, predictive diagnostics, drug research, and clinical decision support systems.
- Organizations are investing heavily in AI-driven automation and analytics to improve operational efficiency, reduce costs, and gain competitive advantages.
- AI and Machine Learning are becoming more accessible due to the availability of user-friendly frameworks, cloud platforms, and open-source tools.
- As AI adoption increases, ethical considerations, including data privacy, fairness, transparency, and responsible AI usage, are receiving greater attention.
- The AI and Machine Learning market is expected to continue strong growth, with expanding use cases in both enterprise solutions and consumer-facing applications.
- The expansion of AI and ML technologies is creating new career opportunities in areas such as AI research, data science, Machine Learning engineering, and analytics.
- There is a rising demand for skilled AI and Machine Learning professionals who can design, deploy, manage, and optimize intelligent systems across various industries.
- Model tuning and optimization is a critical process in AI and Machine Learning, involving the adjustment of algorithms and parameters to ensure accurate, reliable, and efficient results.
Our Great Achievements
AI ML Learners Testimonials
Highlights Of AI ML Course
- Covers essential areas such as Machine Learning, Deep Learning, Natural Language Processing, and AI ethics.
- Includes hands-on projects and real-time case studies to strengthen practical knowledge.
- Training is delivered by highly experienced instructors with strong industry exposure in AI and Machine Learning.
- Suitable for beginners as well as working professionals looking to upgrade their AI skills.
- Offers online and flexible learning options to suit different schedules.
- Students receive access to exclusive AI tools, datasets, and learning resources.
- Provides career guidance, placement assistance, and networking opportunities.
- Successful participants receive a recognized certification from AzureAI Masters.
- Includes important modules such as MLOps, helping learners manage, deploy, and maintain AI models in real-time work environments.
AI ML Course Outline
01
Introduction to Artificial Intelligence and Machine Learning fundamentals and their real-world applications.
02
Core concepts of Machine Learning and Deep Learning, including algorithms, workflows, and model training.
03
In-depth coverage of Machine Learning models and Deep Learning architectures used across industries.
04
Practical experience designing, training, and fine-tuning AI and machine learning models with real-world datasets.
05
Practical projects focused on data analysis, prediction systems, classification, and intelligent automation.
06
Training on ethical AI practices, data privacy, bias handling, and responsible AI usage.
07
Industry-driven case studies that demonstrate practical AI and Machine Learning applications across multiple sectors.
08
Expert guidance on deploying AI models, understanding core MLOps practices, and receiving career support to progress in the AI & ML domain.
Certification
Certifications in Artificial Intelligence and Machine Learning validate an individual’s skills, knowledge, and practical ability to work with intelligent systems that analyze data, learn from patterns, and support decision-making processes. These credentials are highly valued across industries, as they demonstrate strong proficiency in Machine Learning algorithms, Deep Learning techniques, and real-world AI applications.
Earning an AI & Machine Learning certification can significantly enhance career opportunities by improving credibility, strengthening technical profiles, and providing a competitive advantage in the job market. Certified professionals are often considered for advanced roles in data science, AI engineering, machine learning development, and applied research.
Here are some certifications AI ML:
- Popular AI & Machine Learning Certifications
- Google Cloud Professional Data Engineer
- Covers data engineering, Machine Learning pipelines, and AI-based solutions using cloud technologies, with a strong focus on scalable and production-ready systems.
- Deep Learning Specialization – by Andrew Ng
- A comprehensive program that explains Deep Learning fundamentals, neural networks, optimization techniques, and real-world AI use cases.
- Machine Learning and AI Foundations – by Microsoft
- Provides foundational knowledge in Artificial Intelligence and Machine Learning concepts, tools, and applied business scenarios.
- Machine Learning Engineer Nanodegree – by Udacity
- Focuses on building, evaluating, and deploying Machine Learning models using industry-standard workflows and best practices.
- AI Engineering Professional Certificate
- Covers a broad range of AI technologies, including Machine Learning model development, evaluation, and deployment strategies.
- NVIDIA Deep Learning Institute Certifications
- Offers hands-on certifications in Deep Learning, GPU-accelerated computing, and AI performance optimization.
- Stanford University Machine Learning Certificate
- Includes advanced coursework on Machine Learning algorithms, statistical learning, and practical AI methodologies used in industry and research.
Faqs
Artificial Intelligence is the field of computer science that enables machines to simulate human intelligence, such as learning, reasoning, decision-making, and problem-solving.
Machine Learning is a subset of AI that allows systems to learn from data and improve performance over time without being explicitly programmed.
This course is suitable for students, fresh graduates, working professionals, engineers, analysts, and anyone interested in building a career in AI and Machine Learning.
Basic knowledge of Python is recommended, but beginners can also enroll as programming fundamentals are covered at the start.
Yes. The course is designed to gradually build concepts, making it accessible for learners from non-technical backgrounds with proper guidance.
You will gain skills in data analysis, Machine Learning algorithms, Deep Learning, NLP basics, model evaluation, deployment, and MLOps fundamentals.
The course covers Python, NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, SQL, cloud basics, and MLOps tools.
Yes. The course includes multiple hands-on projects and real-world case studies to ensure practical learning.
Yes. You will work with industry-relevant datasets to understand real-time data challenges and solutions.
The course duration typically ranges from 3 to 6 months, depending on the learning mode and batch schedule.
Yes. The course offers online, classroom, and hybrid learning options to suit different schedules.
Yes. Upon successful completion, you will receive an AI & Machine Learning certification recognized by industry professionals.
Yes. The program includes resume building, interview preparation, mock interviews, and job placement support.
This course is suitable for students, fresh graduates, working professionals, engineers, and anyone interested in building a career in AI and Machine Learning.
Basic knowledge of Python is helpful, but beginners can also enroll as the course starts with essential programming and ML fundamentals.
You will learn data analysis, Machine Learning algorithms, Deep Learning basics, NLP concepts, model evaluation, deployment, and MLOps fundamentals.
Yes. You will learn how to deploy Machine Learning models using real-world workflows and cloud-based approaches.
This course emphasizes hands-on learning, real-time projects, industry case studies, and personalized mentorship.
Yes. You will receive career counseling, resume reviews, interview coaching, and job market guidance.
Yes. A free demo session is available to help you understand the course structure, teaching style, and learning outcomes.
