AI and Machine Learning Training in Hyderabad

  • Instruction by experienced industry professionals
  • Interactive live classes with dedicated Q&A sessions
  • Hands-on projects for practical experience and skill development
  • Flexible schedules designed for both students and working professionals
  • AI and machine learning Certification in Hyderabad covering beginner to advanced levels
Hands On   40+ Hrs
Projects   4 +
Placement Support   Lifetime Access
3K+

    Course Fees on Month ₹8999 ₹18000
    (Lowest price in chennai)

    See why over 25,000+ Students choose ACTE

    Curriculam of AI and Machine Learning Training in Hyderabad

    Curriculam Designed By Experts

    Expertly designed curriculum for future-ready professionals.

    Industry Oriented Curriculam

    An exhaustive curriculum designed by our industry experts which will help you to get placed in your dream IT company

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      30+  Case Studies & Projects
    •  
      9+  Engaging Projects
    •  
      10+   Years Of Experience
  • Overview of Artificial Intelligence
  • History and Evolution of AI
  • Types of AI: Narrow, General, and Super AI
  • Introduction to Machine Learning
  • Supervised vs. Unsupervised Learning
  • Applications of AI and ML
  • Ethical Considerations in AI
  • Importance of Data in AI/ML
  • Data Collection Techniques
  • Data Cleaning and Handling Missing Values
  • Data Transformation and Normalization
  • Exploratory Data Analysis (EDA)
  • Linear Regression
  • Logistic Regression
  • Decision Trees
  • Random Forest
  • Support Vector Machines (SVM)
  • K-Nearest Neighbors (KNN)
  • Clustering Techniques: K-Means, Hierarchical
  • Principal Component Analysis (PCA)
  • Anomaly Detection
  • Association Rule Learning
  • Introduction to Neural Networks
  • Perceptron and Multilayer Perceptron
  • Activation Functions
  • Backpropagation Algorithm
  • Convolutional Neural Networks (CNNs)
  • Recurrent Neural Networks (RNNs)
  • Deep Learning Frameworks
  • Introduction to NLP
  • Text Preprocessing Techniques
  • Tokenization and Lemmatization
  • Sentiment Analysis
  • Language Modeling and Transformers
  • Speech Recognition
  • Chatbots and Conversational AI
  • Model Deployment Basics
  • Building APIs for ML Models
  • Cloud Services for Deployment (AWS, Azure, GCP)
  • Monitoring Model Performance
  • Retraining and Updating Models
  • Scalability Considerations
  • Overview of Popular Tools
  • Python Libraries: Scikit-learn, Pandas, NumPy
  • Deep Learning Frameworks
  • Data Visualization Libraries
  • Integrated Development Environments (IDEs)
  • Version Control with Git
  • Ethical Challenges in AI
  • Bias and Fairness in AI Models
  • Privacy Concerns and Data Protection
  • Explainable AI (XAI)
  • AI in Healthcare, Finance, and Other Industries
  • Emerging Trends: AutoML, Federated Learning
  • Show More

    AI and Machine Learning Training Projects

    Become a AI and Machine Learning Expert With Practical and Engaging Projects.

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      Practice essential Tools
    •  
      Designed by Industry experts
    •  
      Get Real-world Experience

    Basic Data Exploration and Visualization

    Collect a dataset (e.g., Iris or Titanic) and perform EDA using Python libraries like Pandas and Matplotlib.

    Simple Linear Regression Model

    Build and evaluate a linear regression model to predict house prices or similar datasets.

    Data Preprocessing Project

    Clean and prepare a raw dataset by handling missing values and normalizing data.

    Decision Tree and Random Forest Classification

    Build and tune decision tree and random forest models on datasets like customer churn or credit scoring.

    Clustering with K-Means

    Perform customer segmentation using K-means clustering on marketing data.

    Neural Network Basics

    Implement a simple feedforward neural network for digit recognition (MNIST dataset).

    Deep Learning with Convolutional Neural Networks

    Build a CNN for image classification tasks (e.g., CIFAR-10 or ImageNet).

    Deploying ML Models

    Create and deploy an ML model using Flask/Django and containerize with Docker.

    Explainable AI (XAI) Implementation

    Use SHAP or LIME to explain predictions of complex models for transparency.

    Key Features

    Practical Training

    Global Certifications

    Flexible Timing

    Trainer Support

    Study Material

    Placement Support

    Mock Interviews

    Resume Building

    Batch Schedule

    Weekdays Regular (Class 1Hr - 1:30Hrs) / Per Session

    • 13 - Oct - 2025 Starts Coming Monday ( Monday - Friday) 08:00 AM (IST)
    • 15 - Oct - 2025 Starts Coming Wednesday ( Monday - Friday) 10:00 AM (IST)

    Weekend Regular (Class 3Hrs) / Per Session

    • 18 - Oct - 2025 Starts Coming Saturday ( Saturday - Sunday) 10:00 AM (IST)

    Weekend Fast-track (Class 6Hrs - 7Hrs) / Per Session

    • 19 - Oct - 2025 Starts Coming Saturday ( Saturday - Sunday) 10:00 AM (IST)

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      • Learning strategies that are appropriate and tailored to your company's requirements.
      • Live projects guided by instructors are a characteristic of the virtual learning environment.
      • The curriculum includes of full-day lectures, practical exercises, and case studies.

      AI and Machine Learning Training Overview

      Benefits Gained from AI and Machine Learning Training in Hyderabad

      • Industry-Relevant Curriculum: Training programs are designed in alignment with current industry needs. Learners gain hands-on experience with real-world tools and datasets. This ensures you're job-ready from day one after completing the course.
      • Expert Guidance and Mentorship: Courses are taught by seasoned professionals with years of AI/ML experience. They offer personalized mentorship and industry insights during training. This bridges the gap between academic learning and practical application.
      • Career Support and Placement Assistance: Many institutes offer resume building, mock interviews, and job referrals. Placement support opens doors to MNCs, startups, and research roles. You also gain access to alumni networks and hiring partners.
      • Practical Projects and Case Studies: Hands-on projects simulate real business problems and scenarios. You learn to apply ML algorithms, NLP, and deep learning models. This practical exposure enhances problem-solving and model deployment skills.

      Emerging Future Trends in AI and Machine Learning Training in Hyderabad

      • Integration with Cloud and Edge Computing: Courses now include training on deploying AI models on cloud platforms. Edge computing and IoT integration are growing in smart city applications. Hyderabad’s tech ecosystem is aligning with these smart technologies.
      • Focus on Responsible and Explainable AI: Ethical AI and explainability are being integrated into training modules. Understanding bias, fairness, and transparency is now essential. This is critical for roles in finance, healthcare, and government projects.
      • Rise of No-Code and AutoML Tools: Training programs now introduce platforms like Google AutoML and H2O.ai. These allow non-programmers to build models quickly. It opens doors for business analysts and domain experts to join the AI revolution.
      • Latest Advancements in AI and ML Course in Hyderabad

        Recent AI and machine learning Certification in Hyderabad have evolved to include deep learning architectures like transformers and generative models (e.g., GPT). Students are trained in advanced tools such as TensorFlow, PyTorch, and LangChain. Cloud-based deployment, model interpretability, and MLOps are now core modules. Institutes are also including real-time analytics, reinforcement learning, and LLM fine-tuning. These updates reflect the region’s increasing demand for cutting-edge AI talent.

        Main Concepts Behind AI and ML Placement in Hyderabad

        AI and ML Course in Hyderabad programs focus on bridging skill gaps by offering hands-on project work, real-world case studies, and mock technical interviews. They emphasize core concepts like supervised learning, neural networks, model tuning, and deployment. Soft skills, resume optimization, and Git portfolio development are also covered. Regular assessments and hackathons simulate job challenges. These programs are structured to make candidates confident, competent, and competitive in the job market.

        Real-Time Projects Completed Recently in AI and ML Placement in Hyderabad

        Several real-time projects have been completed recently in Hyderabad's AI/ML placement tracks. These include predictive models for healthcare diagnostics, real estate price estimation, and fraud detection for fintech apps. Some projects focused on NLP tasks like chatbots, sentiment analysis, and resume screening automation. Deep learning projects in image classification for medical imaging and object detection were also executed. AI and machine learning Certification in Hyderabad capstone projects are often aligned with actual business problems from hiring partners.

      Add-Ons Info

      Career Opportunities  After AI and Machine Learning

      Machine Learning Engineer

      Designs and deploys ML models using algorithms and real-world datasets. Applies statistical methods to build predictive models and automate tasks. Strong coding and model tuning skills are essential for this role.

      Data Scientist

      Analyzes large datasets to uncover insights and drive business decisions. Uses ML, deep learning, and data visualization tools. Works across industries like healthcare, retail, and logistics.

      AI Engineer

      Develops intelligent systems capable of decision-making and automation. Integrates deep learning, NLP, and reinforcement learning techniques. Contributes to the development of chatbots, recommendation engines.

      NLP Specialist

      Focuses on building systems that understand and process human language. Works on sentiment analysis, chatbots, and speech recognition. Often uses Python libraries like NLTK, spaCy, and transformers.

      Computer Vision Engineer

      Builds image and video recognition models using deep learning frameworks. Used in facial recognition, autonomous vehicles, and surveillance tech. Requires experience with CNNs, OpenCV, and TensorFlow or PyTorch.

      AI Product Manager

      Bridges the gap between data science teams and business stakeholders. Translates business needs into AI features and solutions. Manages product roadmaps and assesses model performance.


      Skill to Master
      Supervised and Unsupervised Learning
      Data Preprocessing and Feature Engineering
      Model Evaluation and Hyperparameter Tuning
      Deep Learning with Neural Networks
      Natural Language Processing (NLP)
      Computer Vision and Image Processing
      Data Visualization and Storytelling
      Working with Real-Time Streaming
      Deployment using Flask, FastAPI, or Docker
      Exploratory Data Analysis (EDA)
      Understanding of MLOps & CI/CD for ML
      Problem Solving with Algorithms and Statistics
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      Tools to Master
      Python
      TensorFlow
      PyTorch
      Scikit-learn
      Pandas
      NumPy
      Matplotlib
      Jupyter Notebook
      OpenCV
      NLTK / spaCy
      Docker
      Google Colab
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      Our Instructor

      Learn from certified professionals who are currently working.

      instructor
      Training by

      Ram, having 12+ yrs of experience

      Specialized in: AI and Machine Learning, array formulas.

      Note: Ram excels in constructing and optimizing complex formulas for advanced data manipulation. With his expertise, he can create intricate Excel formulas that streamline data analysis, enhance accuracy, and improve efficiency.

      Job Assistant Program

      We are proud to have participated in more than 40,000 career transfers globally.

      AI and Machine Learning Certification

      Certificate
      GET A SAMPLE CERTIFICATE
    • Validates your skills in cutting-edge AI and ML technologies.
    • Enhances employability in a rapidly growing job market.
    • Builds a strong foundation in algorithms, data handling, and model building.
    • Real-world experience is beneficial but not always mandatory for AI and Machine Learning certification. Many certification programs are designed to accommodate beginners by focusing on foundational knowledge and practical exercises.

      Yes, AI and ML Course Certification guarantee employment. It significantly improves your chances by validating your skills and knowledge, but employers also look for practical experience, problem-solving abilities, and cultural fit.

    • Knowledge of data structures and algorithms.
    • Basic understanding of programming languages like Python or R.
    • Familiarity with mathematical concepts such as linear algebra, calculus, and statistics.
    • Enroll in a recognized AI and Machine Learning training program.
    • Study foundational concepts through lectures and reading materials.
    • Practice coding algorithms and building ML models.
    • Complete hands-on projects to apply theoretical knowledge.
    • Yes, many AI and ML training Course exams are available online through secure, proctored platforms. Candidates can take these exams remotely, which offers flexibility and accessibility.

      Practical experience is highly recommended to grasp AI and Machine Learning concepts fully, though it may not be a strict requirement for certification. Hands-on experience through projects, internships, or labs helps translate theoretical knowledge into real-world problem-solving skills.

    • Ability to work on innovative technologies shaping the future.
    • Competitive salaries and career advancement prospects.
    • Enhances problem-solving and analytical thinking skills.
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      Frequently Asked Questions

      • Yes, AI and ML training institute offer both in-person classroom sessions and live online classes to suit different learning preferences.
      • The typical duration of an AI and Machine Learning course ranges from 3 to 6 months, depending on the depth of the curriculum and mode of study
      • Some accelerated or specialized courses may be completed in 8 to 12 weeks, while more comprehensive programs can extend up to 1 year for advanced learning
      • The placement assistance process typically includes resume building, where experts help tailor your CV to highlight relevant skills and projects.
      • You’ll receive mock interview sessions to practice technical and HR questions, boosting your confidence
      • Absolutely, AI and ML training institute includes hands-on projects based on real-world data sets and industry scenarios to enhance practical skills.
      • Yes, dedicated sessions for interview preparation and soft skills training are part of the course to boost your confidence.

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      • Flexibility: Online, weekends & more.
      • Hands-on: Projects & practical exercises.
      • Placement support: Resume & interview help.
      • Lifelong learning: Valuable & adaptable skills.
      • Full curriculum: Foundational & advanced concepts.

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