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Artificial Intelligence Course Features

ARTIFICIAL INTELLIGENCE LEAD MENTORS

ARTIFICIAL INTELLIGENCE COURSE FEE IN HYDERABAD

Live Virtual

Instructor Led Live Online

154,000
81,900

  • IABAC® & DMC Certification
  • 9-Month | 780 Learning Hours
  • 100-Hour Live Online Training
  • 10 Capstone & 1 Client Project
  • 365 Days Flexi Pass + Cloud Lab
  • Internship + Job Assistance

Blended Learning

Self Learning + Live Mentoring

92,000
57,900

  • Self Learning + Live Mentoring
  • IABAC® & DMC Certification
  • 1 Year Access To Elearning
  • 10 Capstone & 1 Client Project
  • Job Assistance
  • 24*7 Learner assistance and support

Classroom

In - Person Classroom Training

154,000
86,900

  • IABAC® & DMC Certification
  • 9-Month | 780 Learning Hours
  • 100-Hour Classroom Sessions
  • 10 Capstone & 1 Client Project
  • Cloud Lab Access
  • Internship + Job Assistance

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SYLLABUS OF AI COURSE IN HYDERABAD

MODULE 1 : ARTIFICIAL INTELLIGENCE OVERVIEW 

• Evolution Of Human Intelligence
• What Is Artificial Intelligence?
• History Of Artificial Intelligence
• Why Artificial Intelligence Now?
• Areas Of Artificial Intelligence
• AI Vs Data Science Vs Machine Learning

MODULE 2 :  DEEP LEARNING INTRODUCTION

• Deep Neural Network
• Machine Learning vs Deep Learning
• Feature Learning in Deep Networks
• Applications of Deep Learning Networks

MODULE3 : TENSORFLOW FOUNDATION

• TensorFlow Structure and Modules
• Hands-On:ML modeling with TensorFlow

MODULE 4 : COMPUTER VISION INTRODUCTION

• Image Basics
• Convolution Neural Network (CNN)
• Image Classification with CNN
• Hands-On: Cat vs Dogs Classification with CNN Network

MODULE 5 : NATURAL LANGUAGE PROCESSING (NLP)

• NLP Introduction
• Bag of Words Models
• Word Embedding
• Hands-On:BERT Algorithm

MODULE 6 : AI ETHICAL ISSUES AND CONCERNS

• Issues And Concerns Around Ai
• Ai And Ethical Concerns
• Ai And Bias
• Ai:Ethics, Bias, And Trust

MODULE 1 : PYTHON BASICS 

 • Introduction of python
 • Installation of Python and IDE
 • Python Variables
 • Python basic data types
 • Number & Booleans, strings
 • Arithmetic Operators
 • Comparison Operators
 • Assignment Operators

MODULE 2 : PYTHON CONTROL STATEMENTS 

 • IF Conditional statement
 • IF-ELSE
 • NESTED IF
 • Python Loops basics
 • WHILE Statement
 • FOR statements
 • BREAK and CONTINUE statements

MODULE 3 : PYTHON DATA STRUCTURES 

 • Basic data structure in python
 • Basics of List
 • List: Object, methods
 • Tuple: Object, methods
 • Sets: Object, methods
 • Dictionary: Object, methods

MODULE 4 : PYTHON FUNCTIONS 

 • Functions basics
 • Function Parameter passing
 • Lambda functions
 • Map, reduce, filter functions

MODULE 1 : OVERVIEW OF STATISTICS 

 • Introduction to Statistics
 • Descriptive And Inferential Statistics
 • Basic Terms Of Statistics
 • Types Of Data

MODULE 2 : HARNESSING DATA 

 • Random Sampling
 • Sampling With Replacement And Without Replacement
 • Cochran's Minimum Sample Size
 • Types of Sampling
 • Simple Random Sampling
 • Stratified Random Sampling
 • Cluster Random Sampling
 • Systematic Random Sampling
 • Multi stage Sampling
 • Sampling Error
 • Methods Of Collecting Data

MODULE 3 : EXPLORATORY DATA ANALYSIS 

 • Exploratory Data Analysis Introduction
 • Measures Of Central Tendencies: Mean,Median And Mode
 • Measures Of Central Tendencies: Range, Variance And Standard Deviation
 • Data Distribution Plot: Histogram
 • Normal Distribution & Properties
 • Z Value / Standard Value
 • Empherical Rule and Outliers
 • Central Limit Theorem
 • Normality Testing
 • Skewness & Kurtosis
 • Measures Of Distance: Euclidean, Manhattan And Minkowski Distance
 • Covariance & Correlation

MODULE 4 : HYPOTHESIS TESTING 

 • Hypothesis Testing Introduction
 • P- Value, Critical Region
 • Types of Hypothesis Testing
 • Hypothesis Testing Errors : Type I And Type II
 • Two Sample Independent T-test
 • Two Sample Relation T-test
 • One Way Anova Test
 • Application of Hypothesis testing

MODULE 1: MACHINE LEARNING INTRODUCTION 

 • What Is ML? ML Vs AI
 • Clustering, Classification And Regression
 • Supervised Vs Unsupervised

MODULE 2: PYTHON NUMPY  PACKAGE 

• Introduction to Numpy Package
 • Array as Data Structure
 • Core Numpy functions
 • Matrix Operations, Broadcasting in Arrays

MODULE 3: PYTHON PANDAS PACKAGE

 • Introduction to Pandas package
 • Series in Pandas
 • Data Frame in Pandas
 • File Reading in Pandas
 • Data munging with Pandas

MODULE 4:  VISUALIZATION WITH PYTHON - Matplotlib 

 • Visualization Packages (Matplotlib)
 • Components Of A Plot, Sub-Plots
 • Basic Plots: Line, Bar, Pie, Scatter

MODULE 5: PYTHON VISUALIZATION PACKAGE - SEABORN

 • Seaborn: Basic Plot
 • Advanced Python Data Visualizations

MODULE 6: ML ALGO: LINEAR REGRESSION

 • Introduction to Linear Regression
 • How it works: Regression and Best Fit Line
 • Modeling and Evaluation in Python

MODULE 7: ML ALGO: LOGISTIC REGRESSION 

 • Introduction to Logistic Regression
 • How it works: Classification & Sigmoid Curve
 • Modeling and Evaluation in Python

MODULE 8: ML ALGO: K MEANS CLUSTERING

 • Understanding Clustering (Unsupervised)
 • K Means Algorithm
 • How it works : K Means theory
 • Modeling in Python

MODULE 9: ML ALGO: KNN

 • Introduction to KNN
 • How It Works: Nearest Neighbor Concept
 • Modeling and Evaluation in Python

MODULE 1:  FEATURE ENGINEERING 

 • Introduction to Feature Engineering
 • Feature Engineering Techniques: Encoding, Scaling, Data Transformation
 • Handling Missing values, handling outliers
 • Creation of Pipeline
 • Use case for feature engineering

MODULE 2: ML ALGO: SUPPORT VECTOR MACHINE (SVM)

 • Introduction to SVM
 • How It Works: SVM Concept, Kernel Trick
 • Modeling and Evaluation of SVM in Python

MODULE 3: PRINCIPAL COMPONENT ANALYSIS (PCA)

 • Building Blocks Of PCA
 • How it works: Finding Principal Components
 • Modeling PCA in Python

MODULE 4: ML ALGO: DECISION TREE 

 • Introduction to Decision Tree & Random Forest
 • How it works
 • Modeling and Evaluation in Python

MODULE 5: ENSEMBLE TECHNIQUES - BAGGING

 • Introduction to Ensemble technique 
 • Bagging and How it works
 • Modeling and Evaluation in Python

MODULE 6: ML ALGO: NAÏVE BAYES

 • Introduction to Naive Bayes
 • How it works: Bayes' Theorem
 • Naive Bayes For Text Classification
 • Modeling and Evaluation in Python

MODULE 7:  GRADIENT BOOSTING, XGBOOST 

 • Introduction to Boosting and XGBoost
 • How it works?
 • Modeling and Evaluation of in Python

MODULE 1: TIME SERIES FORECASTING - ARIMA 

 • What is Time Series?
 • Trend, Seasonality, cyclical and random
 • Stationarity of Time Series
 • Autoregressive Model (AR)
 • Moving Average Model (MA)
 • ARIMA Model
 • Autocorrelation and AIC
 • Time Series Analysis in Python

MODULE 2:  SENTIMENT ANALYSIS

 • Introduction to Sentiment Analysis
 • NLTK Package
 • Case study: Sentiment Analysis on Movie Reviews

MODULE 3:  REGULAR EXPRESSIONS WITH PYTHON 

 • Regex Introduction
 • Regex codes
 • Text extraction with Python Regex

MODULE 4: ML MODEL DEPLOYMENT WITH FLASK 

 • Introduction to Flask
 • URL and App routing
 • Flask application – ML Model deployment

MODULE 5: ADVANCED DATA ANALYSIS WITH MS EXCEL 

 • MS Excel core Functions
 • Advanced Functions (VLOOKUP, INDIRECT..)
 • Linear Regression with EXCEL
 • Data Table
 • Goal Seek Analysis
 • Pivot Table
 • Solving Data Equation with EXCEL

MODULE 6:  AWS CLOUD FOR DATA SCIENCE

 • Introduction of cloud
 • Difference between GCC, Azure,AWS
 • AWS Service ( EC2 instance)

MODULE 7: AZURE FOR DATA SCIENCE

 • Introduction to AZURE ML studio
 • Data Pipeline
 • ML modeling with Azure

MODULE 8: INTRODUCTION TO DEEP LEARNING

 • Introduction to Artificial Neural Network, Architecture
 • Artificial Neural Network in Python
 • Introduction to Convolutional Neural Network, Architecture
 • Convolutional Neural Network in Python

MODULE 1: DATABASE INTRODUCTION

 • DATABASE Overview
 • Key concepts of database management
 • Relational Database Management System
 • CRUD operations

 MODULE 2: SQL BASICS

 • Introduction to Databases
 • Introduction to SQL
 • SQL Commands
 • MY SQL workbench installation

MODULE 3: DATA TYPES AND CONSTRAINTS

 • Numeric, Character, date time data type
 • Primary key, Foreign key, Not null
 • Unique, Check, default, Auto increment

MODULE 4: DATABASES AND TABLES (MySQL)

 • Create database
 • Delete database
 • Show and use databases
 • Create table, Rename table
 • Delete table, Delete table records
 • Create new table from existing data types
 • Insert into, Update records
 • Alter table

MODULE 5: SQL JOINS

• Inner join
• Outer join
• Left join
• Right join
• Cross join
• Self join
• Windows functions: Over, Partition , Rank 

MODULE 6: SQL COMMANDS AND CLAUSES

 • Select, Select distinct
 • Aliases, Where clause
 • Relational operators, Logical
 • Between, Order by, In
 • Like, Limit, null/not null, group by
 • Having, Sub queries

 MODULE 7: DOCUMENT DB/NO-SQL DB

 • Introduction of Document DB
 • Document DB vs SQL DB
 • Popular Document DBs
 • MongoDB basics
 • Data format and Key methods

MODULE 1: GIT  INTRODUCTION 

 • Purpose of Version Control
 • Popular Version control tools
 • Git Distribution Version Control
 • Terminologies
 • Git Workflow
 • Git Architecture

MODULE 2: GIT REPOSITORY and GitHub 

 • Git Repo Introduction
 • Create New Repo with Init command
 • Git Essentials: Copy & User Setup
 • Mastering Git and GitHub

MODULE 3: COMMITS, PULL, FETCH AND PUSH 

• Code commits
• Pull, Fetch and conflicts resolution
• Pushing to Remote Repo

MODULE 4: TAGGING, BRANCHING AND MERGING 

• Organize code with branches
• Checkout branch
• Merge branches
• Editing Commits
• Commit command Amend flag
• Git reset and revert

MODULE 5: GIT WITH GITHUB AND BITBUCKET 

• Creating GitHub Account
• Local and Remote Repo
• Collaborating with other developers

MODULE 1: BIG DATA INTRODUCTION 

  • Big Data Overview
  • Five Vs of Big Data
  • What is Big Data and Hadoop
  • Introduction to Hadoop
  • Components of Hadoop Ecosystem
  • Big Data Analytics Introduction

MODULE 2: HDFS AND MAP REDUCE 

  • HDFS – Big Data Storage
  • Distributed Processing with Map Reduce
  • Mapping and reducing  stages concepts
  • Key Terms: Output Format, Partitioners, Combiners, Shuffle, and Sort

MODULE 3: PYSPARK FOUNDATION 

  • PySpark Introduction
  • Spark Configuration
  • Resilient distributed datasets (RDD)
  • Working with RDDs in PySpark
  • Aggregating Data with Pair RDDs

MODULE 4: SPARK SQL and HADOOP HIVE 

  • Introducing Spark SQL
  • Spark SQL vs Hadoop Hive

MODULE 1: TABLEAU FUNDAMENTALS 

 • Introduction to Business Intelligence & Introduction to Tableau
 • Interface Tour, Data visualization: Pie chart, Column chart, Bar chart.
 • Bar chart, Tree Map, Line Chart
 • Area chart, Combination Charts, Map
 • Dashboards creation, Quick Filters
 • Create Table Calculations
 • Create Calculated Fields
 • Create Custom Hierarchies

MODULE 2: POWER-BI BASICS 

 • Power BI Introduction 
 • Basics Visualizations
 • Dashboard Creation
 • Basic Data Cleaning
 • Basic DAX FUNCTION

MODULE 3 : DATA TRANSFORMATION TECHNIQUES

 • Exploring Query Editor
 • Data Cleansing and Manipulation:
 • Creating Our Initial Project File
 • Connecting to Our Data Source
 • Editing Rows
 • Changing Data Types
 • Replacing Values

MODULE 4 :  CONNECTING TO VARIOUS DATA SOURCES 

 • Connecting to a CSV File
 • Connecting to a Webpage
 • Extracting Characters
 • Splitting and Merging Columns
 • Creating Conditional Columns
 • Creating Columns from Examples
 • Create Data Model

MODULE 1: NEURAL NETWORKS 

 • Structure of neural networks
 • Neural network - core concepts(Weight initialization)
 • Neural network - core concepts(Optimizer)
 • Neural network - core concepts(Need of activation)
 • Neural network - core concepts(MSE & RMSE)
 • Feed forward algorithm
 • Backpropagation

MODULE 2: IMPLEMENTING DEEP NEURAL NETWORKS 

 • Introduction to neural networks with tf2.X
 • Simple deep learning model in Keras (tf2.X)
 • Building neural network model in TF2.0 for MNIST dataset

MODULE 3: DEEP COMPUTER VISION - IMAGE RECOGNITION

• Convolutional neural networks (CNNs)
• CNNs with Keras-part1
• CNNs with Keras-part2
• Transfer learning in CNN
• Flowers dataset with tf2.X(part-1)
• Flowers dataset with tf2.X(part-2)
• Examining x-ray with CNN model

MODULE 4 : DEEP COMPUTER VISION - OBJECT DETECTION

 • What is Object detection
 • Methods of Object Detections
 • Metrics of Object detection
 • Bounding Box regression
 • labelimg
 • RCNN
 • Fast RCNN
 • Faster RCNN
 • SSD
 • YOLO Implementation
 • Object detection using cv2

MODULE 5: RECURRENT NEURAL NETWORK 

• RNN introduction
• Sequences with RNNs
• Long short-term memory networks(part 1)
• Long short-term memory networks(part 2)
• Bi-directional RNN and LSTM
• Examples of RNN applications

MODULE 6: NATURAL LANGUAGE PROCESSING (NLP)

• Introduction to Natural language processing
• Working with Text file
• Working with pdf file
• Introduction to regex
• Regex part 1
• Regex part 2
• Word Embedding
• RNN model creation
• Transformers and BERT
• Introduction to GPT (Generative Pre-trained Transformer)
• State of art NLP and projects

MODULE 7: PROMPT ENGINEERING

• Introduction to Prompt Engineering
• Understanding the Role of Prompts in AI Systems
• Design Principles for Effective Prompts
• Techniques for Generating and Optimizing Prompts
• Applications of Prompt Engineering in Natural Language Processing

MODULE 8: REINFORCEMENT LEARNING

• Markov decision process
• Fundamental equations in RL
• Model-based method
• Dynamic programming model free methods

MODULE 9: DEEP REINFORCEMENT LEARNING

• Architectures of deep Q learning
• Deep Q learning
• Reinforcement Learning Projects with OpenAI Gym

MODULE 10: Gen AI

• Gan introduction, Core Concepts, and Applications
• Core concepts of GAN
• GAN applications
• Building GAN model with TensorFlow 2.X
• Introduction to GPT (Generative Pre-trained Transformer)
• Building a Question answer bot with the models on Hugging Face

MODULE 11: Gen AI

• Introduction to Autoencoder
• Basic Structure and Components of Autoencoders
• Types of Autoencoders: Vanilla, Denoising, Variational, Sparse, and Convolutional Autoencoders
• Training Autoencoders: Loss Functions, Optimization Techniques
• Applications of Autoencoders: Dimensionality Reduction, Anomaly Detection, Image

OFFERED ARTIFICIAL INTELLIGENCE COURSES IN HYDERABAD

ARTIFICIAL INTELLIGENCE TRAINING REVIEWS

ABOUT ARTIFICIAL INTELLIGENCE TRAINING IN HYDERABAD

According to Grand View Research, the global artificial intelligence market size was valued at USD 279,220.1 million in 2024 and is projected to reach USD 1,811,747.3 million by 2030, growing at a remarkable from 2025 to 2030. This rapid expansion highlights the urgent demand for skilled professionals in the AI domain.The Artificial Intelligence Course in Hyderabad by Datamites provides the perfect platform to launch a rewarding career in this high-growth field. Designed to meet industry standards, the course equips you with hands-on experience, real-world projects, and mentorship from AI experts.

DataMites offers an industry-recognized Artificial Intelligence Engineer Course, accredited by IABAC and NASSCOM FutureSkills, global-standard training. Spanning 9 months, this comprehensive program was conducted at DataMites offline center in Madhapur, Hyderabad, combining face-to-face learning with hands-on experience. Designed for both aspiring professionals and students, the course features real-time projects, internships, and personalized training. With strong placement assistance, learners are empowered to build successful careers in the rapidly growing field of Artificial Intelligence Certification in Hyderabad.

A recent study by PwC projects that Artificial Intelligence will add a staggering 15.7 trillion Dollar to the global economy by 2030, highlighting its profound impact across industries. Aligning with this technological shift, DataMites provides in-depth offline Artificial Intelligence Training in Hyderabad, featuring practical internships and dedicated career support. This program is meticulously crafted to develop future-ready data science professionals, well-prepared to excel in the ever-evolving world of AI.

Hyderabad has rapidly evolved into one of India’s leading tech and innovation hubs, making it an ideal destination for learning Artificial Intelligence Courses. Home to global IT giants, thriving startups, and top research institutions, the city offers a rich ecosystem for AI education and career growth. Areas like HITEC City and Madhapur are buzzing with opportunities, from cutting-edge AI projects to networking with industry professionals. With its vibrant tech community, affordable living costs, and growing demand for AI talent, Hyderabad provides the perfect environment to gain practical skills and launch a successful career in artificial intelligence.

As reported by Fortune Business Insights, the global Artificial Intelligence market was estimated at USD 515.31 billion in 2023 and is projected to rise to USD 621.19 billion in 2024, eventually soaring to an incredible USD 2,740.46 billion by 2032. With an impressive compound annual growth rate, Artificial Intelligence Training is set to revolutionize industries worldwide. At the heart of this technological surge is Hyderabad, a rapidly growing innovation hub that's attracting international tech leaders and accelerating the adoption of AI across sectors.

Why Choose an Artificial Intelligence Course in Hyderabad?

Hyderabad has quickly emerged as a powerhouse for technology and innovation, making it one of the top destinations in India to pursue Artificial Intelligence Course in Hyderabad. Often dubbed as "Cyberabad," the city is home to a thriving tech ecosystem with global IT giants, AI startups, and R&D centers establishing a strong presence here.

  1. Tech Hub of India: Hyderabad has firmly established itself as one of India’s premier technology centers. Major global tech giants such as Google, Microsoft, Amazon, Facebook, and Apple have set up large-scale operations in the city, creating a vibrant ecosystem for innovation.
  2. Startup Ecosystem: Hyderabad boasts a rapidly expanding startup scene driven by innovation and entrepreneurial spirit. With incubators like T-Hub, WE-Hub, and IIIT-H’s Centre for Innovation & Entrepreneurship, the city encourages experimentation and cutting-edge research in AI, machine learning, and data science courses.
  3. Cost-Effective Learning Environment: Unlike other major Indian metros such as Bengaluru, Mumbai, or Delhi, Hyderabad offers a more affordable cost of living without compromising on quality of life or educational infrastructure. From reasonable housing and transport to budget-friendly food and leisure options, the city is well-suited for students and working professionals looking to upskill in AI without financial strain.
  4. Rapidly Growing AI Job Market: Hyderabad’s strong and evolving AI landscape is driving a surge in demand for talented professionals across a range of roles, including AI Engineers, Data Scientists, Machine Learning Experts, NLP Developers, and AI Researchers. With tech companies actively seeking AI talent, the city offers promising career prospects. As per data from Glassdoor, AI Engineers in Hyderabad earn an average annual salary of around 10 lakhs, reflecting the high value placed on expertise in this cutting-edge field.

In-Demand AI Job Roles in Hyderabad

  1. Artificial Intelligence Engineer: Develops and implements AI models and algorithms to solve complex problems across industries.
  2. Data Scientist: Analyzes and interprets large datasets to extract meaningful insights and support AI-driven decision-making.
  3. Machine Learning Engineer: Designs, builds, and optimizes machine learning models for automation and predictive analytics.
  4. AI Research Scientist: Conducts advanced research to innovate new AI technologies and improve existing models.
  5. Natural Language Processing (NLP) Developer: Works on enabling machines to understand, interpret, and generate human language effectively.

Essential Skills for Key AI Job Roles in Hyderabad

  1. Programming Languages: Programming is the backbone of Artificial Intelligence development. Languages like Python dominate the AI landscape due to their simplicity and extensive libraries (such as TensorFlow, PyTorch, Scikit-learn) that streamline AI model building.
  2. Mathematics & Statistics: A solid grasp of mathematics is essential for understanding how AI algorithms work under the hood.
  3. Machine Learning: Machine Learning (ML) is a core subset of AI focused on building systems that learn from data without explicit programming.
  4. Deep Learning: Deep Learning is a specialized branch of ML that uses artificial neural networks to model complex patterns in large datasets.
  5. Problem Solving & Analytical Thinking: AI professionals must approach challenges with strong analytical skills to break down complex problems into manageable parts. This involves selecting appropriate algorithms, preprocessing data effectively, and interpreting model results critically.

Why Choose DataMites for AI Training in Hyderabad?

When it comes to choosing the best artificial intelligence institute in Hyderabad, DataMites stands out as a trusted name for quality training, hands-on learning, and real-world preparation. Whether you're a beginner or a professional, here's why DataMites is the top choice for AI training in Hyderabad:

  1. Internship Opportunities: Gain practical exposure through internship programs that help bridge the gap between theory and application. These internships add significant value to your portfolio.
  2. Placement Assistance: DataMites provides end-to-end placement support, including resume building, interview coaching, mock sessions, and connections with hiring partners across Hyderabad's tech ecosystem.
  3. Real-Time Projects & Case Studies: Gain real-world experience through 10 live capstone projects and 1 client project. This hands-on approach effectively bridges the gap between academic learning and industry requirements.
  4. Globally Recognized Certifications: The Artificial Intelligence Engineer Certification in Hyderabad by DataMites is accredited by IABAC and NASSCOM FutureSkills, ensuring compliance with international standards.
  5. Comprehensive Curriculum: The Artificial Intelligence course in Hyderabad at DataMites covers Python Course, machine learning, deep learning, computer vision, and NLP, along with real-time projects and case studies.
  6. Flexible Learning Modes: DataMites offers offline AI courses in Hyderabad with classroom training sessions, hands-on labs, and one-on-one mentoring.
  7. Industry-Expert Trainers: At DataMites, you learn from AI professionals who bring years of industry experience from leading tech firms. 

With 100,000 learners trained and a proven track record, DataMites has become a go-to institute for artificial intelligence training in Hyderabad. It’s more than just a course, it's a career transformation.

DataMites Offline Centers for In-Person Learning

DataMites offers offline artificial intelligence training in Hyderabad, other offline locations include Bangalore, Pune, Chennai, Delhi, Kolkata, Coimbatore, Mumbai, Ahmedabad, Chandigarh, and Mumbai, equipped with modern infrastructure and accessible locations. Interact with peers, work on collaborative projects, and engage directly with faculty for a more immersive experience. 

DataMites offline centre in Hyderabad

The Offline Artificial Intelligence Certification in Hyderabad by DataMites is conducted at the Madhapur centre: 313, 4th Floor, Ayyappa Society Main Road, Ayyappa Society, Megha Hills, Madhapur, Hyderabad, Telangana 500081

The DataMites Artificial Intelligence Course in Hyderabad is designed for fresh graduates, working professionals, career changers, and anyone passionate about data. With a strong emphasis on practical, industry-relevant skills, the Madhapur centre is easily accessible from key localities such as: Hitec City (500081), Gachibowli(500032), Kavuri hills(500033),  Kothaguda(500084), Anjaneya Nagar(500072), Kondapur(500084), Kokapet(500075), Mehdipatnam(500028), Miyapur(500049), Dammaiguda(500083), AttaPur(500048), Balapur(500005), Manikonda(500089), Jubilee Hills(500033), Banjara Hills(500034), Kukatpally(500072), and Ameerpet (500018) can conveniently access the Madhapur center for offline classes at DataMites.

3-Phase Learning Methodology at DataMites

DataMites follows a comprehensive 3-Phase Learning Methodology designed to deliver a deep and practical AI learning experience.

Phase 1: Pre-Course Preparation: Learners start with access to curated video tutorials and study resources that build a strong foundational understanding of artificial intelligence fundamentals.

Phase 2: Intensive Training: Over three months, students participate in 20 hours of weekly sessions, choosing between live online classes or in-person training at DataMites Hyderabad center. This phase emphasizes hands-on projects, expert mentorship, and industry-aligned curriculum to enhance practical skills.

Phase 3: Internship and Career Support: In the final phase, participants work on 10 capstone projects along with a client-based assignment, earning a valuable internship certificate. DataMites Placement Assistance Team provides personalized career support, helping learners secure positions with top companies in the AI field.

Hyderabad stands out as a thriving hub for Artificial Intelligence training, offering a wide range of in-demand career opportunities such as AI engineers, machine learning experts, data scientists, and AI product managers. These roles are key drivers behind the city’s reputation as a hotspot for innovative AI research and development.

With AI adoption accelerating across industries, the need for skilled professionals is growing rapidly. DataMites Training Institute in Hyderabad delivers a comprehensive learning journey designed to equip you with the skills needed to excel in this dynamic field. Our internationally accredited programs cover Artificial Intelligence Training, data science, data analytics course, machine learning, and data engineering. By joining DataMites, you position yourself at the forefront of the AI revolution, ready to contribute to the technological breakthroughs that are shaping tomorrow’s world.

DESCRIPTION OF ARTIFICIAL INTELLIGENCE COURSE IN HYDERABAD

The scope of Artificial Intelligence in Hyderabad's job market is rapidly expanding, with increasing demand for skilled professionals across IT, healthcare, finance, and startups driven by the city's thriving tech ecosystem.

Why should you pursue an Artificial Intelligence course in Hyderabad because the city offers top-tier training institutes, access to expert mentors, and abundant job opportunities in a rapidly growing AI-driven tech industry.

An AI course in Hyderabad teaches key skills such as Python programming, machine learning, deep learning, natural language processing (NLP), data analysis, and real-time project development.

Anyone interested in AI, including students, working professionals, career changers, and entrepreneurs from both technical and non-technical backgrounds, can enroll in the Artificial Intelligence training program in Hyderabad.

An AI course in Hyderabad typically spans 3 to 9 months and costs between INR 70,000 to INR 2,50,000, depending on the program's depth, training mode (online/offline/blended), course add-ons, and offers. EMI and scholarships may also be available.

Some of the technical skills that would prove advantageous in learning an Artificial Intelligence course are:-

  • Knowledge of Mathematics and Statistics.

  • Knowledge of Algorithms.

  • Knowledge of programming languages- C, C++, Java

  • Knowledge of Neural Networks

  • Knowledge of Natural Language Processing- NLP Libraries

The demand for an Artificial Intelligence course in Hyderabad is soaring, with over 2,000 AI-related job openings in 2025 and a 35–40% annual growth rate in AI roles across industries such as IT, healthcare, finance, and startups

After completing an AI course in Hyderabad, you can pursue career opportunities as an AI Engineer, Machine Learning Engineer, Data Scientist, NLP Engineer, Deep Learning Specialist, or Business Intelligence Analyst in top tech companies and startups.

The AI program teaches tools and technologies such as Python, TensorFlow, Keras, Scikit-learn, Pandas, NumPy, OpenCV, NLTK, and cloud platforms like AWS or Google Cloud.

Industries such as IT, healthcare, finance, e-commerce, pharmaceuticals, and smart city infrastructure in Hyderabad are actively hiring AI professionals.

No, prior coding knowledge is not mandatory, as most AI courses in Hyderabad include beginner-friendly programming training, especially in Python.

Hyderabad is becoming a growing hub for AI due to its strong IT ecosystem, government-backed tech initiatives, availability of skilled talent, and presence of multinational companies.

Artificial Intelligence enhances productivity, enables automation, improves decision-making, personalizes user experiences, and solves complex problems across various sectors.

Machine learning is a core subset of AI that allows systems to learn from data and make decisions or predictions without explicit programming.

Computer vision enables AI systems to interpret, analyze, and make decisions based on visual data like images and videos.

AI significantly impacts healthcare, finance, education, transportation, retail, manufacturing, entertainment, and cybersecurity.

Generative AI refers to AI models that create content such as text, images, audio, and code, and it's used in industries like media, marketing, healthcare, design, and software development.

Python is the most widely used and recommended programming language for AI due to its simplicity and extensive library support.

While not compulsory at the start, learning to code is essential for developing and implementing AI models effectively.

The future of artificial intelligence promises exponential growth in automation, personalization, and innovation across every major industry, transforming how we live and work.

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FAQ’S OF ARTIFICIAL INTELLIGENCE TRAINING IN HYDERABAD

DataMites provides globally recognized AI certification accredited by IABAC upon course completion.

DataMites is preferred for its expert trainers, comprehensive curriculum, hands-on projects, and strong placement support.

Yes, DataMites offers internship opportunities to provide practical industry experience during the AI course.

Yes, DataMites provides flexible EMI plans to make Artificial Intelligence training in Hyderabad affordable for all learners.

Yes, DataMites offers free trial classes so prospective students can experience the training before enrolling.

Yes. DataMites offers internship opportunities for the Artificial Intelligence course which helps you to get exposure,  understand and implement the concepts learned in the course to build AI models for solving real-world problems. DataMites provides 10 Capstone projects and 1 client project for the Artificial Intelligence course.

Yes. You will learn Deep Learning as a part of the AI Engineer course. It includes - Layers, Loss Function, Optimization, Model Training, and Evaluation, etc.

Yes. You will learn Computer Vision as a part of the Artificial Intelligence course. It includes - Convolutional Neural Networks, CNN with KERAS, Transfer Learning, etc.

Yes. You will learn Neural Networks as a part of the Artificial Intelligence course. It includes - Core Concepts of Neural Networks, Structure of Neural Networks, Back Propagation, etc.

The Artificial Intelligence course offered by DataMites in Hyderabad covers the following topics:-

  • Artificial Intelligence Foundation.

  • Machine Learning 

  • Tensorflow

  • Core Learning Algorithms 

  • Neural Networks

  • Natural Language Processing(NLP)

  • Deep Computer Vision- Convolutional Neural Networks

  • Reinforcement Learning.

The duration of the Artificial Intelligence course provided by DataMites in Hyderabad is 6 months with 120 hrs of live online training conducted by industry experts.

Artificial Intelligence is a vast subject for study, it is a mix of Statistics and Computer Science. DataMites in Hyderabad offers quality training sessions in Artificial Intelligence, Machine Learning, etc. The Artificial Intelligence courses provided by DataMites in Hyderabad are exclusively designed in tune with the current industry requirements. Also with many projects to work on, under the mentoring of industry experts.

DataMites offers an Artificial Intelligence course in Hyderabad in three different modes. The Live Virtual/Online and Classroom training is offered at a fee/cost of Rs 99000/-, and the Self Learning mode is offered at Rs 69000/-.

The registrations cancelled within 48 hrs of enrollment will be refunded in full. The processing time of the refund is within 30 days, from the date of the receipt of the cancellation request

You have access to the online study materials from 6 months up to 1 year.

DataMites accepts all the online payments(Debit/Credit)for the AI course in Hyderabad through Razor pay. If you opt to pay through your credit card there will be an EMI option. DataMites collect token advance during the time of registration and the remaining payment should be settled in full before the completion of the course.

All the online sessions are recorded. If you happen to miss a session you can access the online recording.

Yes. The Artificial Intelligence certification exam fee is included in the total course fee. Therefore once you are registered for a course, you are also eligible to attend the exam.

Yes. You will learn Natural Language Processing(NLP) as a part of the Artificial Intelligence course. It includes - The Basics of Natural Language Processing, Integer Coding, Word Embedding, and Bag Of Words.

Yes. One of the courses out of the bundle of AI course talks about Reinforcement Learning. It includes- Markov Decision Process, Fundamental Equations in Reinforcement Learning.

Yes. One of the courses out of the bundle of AI course talks about Tensorflow. It includes-Basics of Tensorflow, Installation and Basic Operation in Tensorflow, Tensorflow 2.0 Eager Mode.

Yes. One of the courses out of the bundle of AI course talks about Machine Learning. It includes-Basics of Machine Learning, Mathematics for Machine Learning.

Yes. One of the courses out of the bundle of AI course talks about Python. It includes-

Yes, the  Artificial Intelligence Engineer course provided by DataMites comprises a topic on Machine Learning in the syllabus. Therefore when you learn the AI course, you also get an opportunity to learn Machine Learning. The Machine Learning topics covered are:-

Machine Learning Overview, Mathematics for Machine Learning, Advanced Machine Learning Concepts, etc.

Yes. DataMites will provide you with a course completion certificate after you clear the AI certification examination.

The AI course offered by DataMites in Hyderabad includes 10 capstone projects and 1 client project.

The mode of training offered by DataMites in Hyderabad is primarily online. However, classroom training can be made available in Hyderabad,  if there is adequate demand for the same.

DataMites is a global institute for Artificial Intelligence education. It has a history of training for more than 15000 candidates. The syllabus provided by DataMites in Hyderabad is exclusively designed in tune with the current industry trends. The following makes DataMites unique from others:-

  • Globally Recognised Certification- IABAC 

  • Experienced Trainers

  • Industry aligned courses

  • Internship Opportunities

  • Career Guidance

  • More than 15000 certified learners

DataMites provides Flexi Pass, which gives you the privilege to attend unlimited batches in a year. The Flexi Pass is specific to one particular course. Therefore if you have a Flexi pass for a particular course of your choice, you will be able to attend any number of sessions of that course. It is to be noted that a Flexi pass is valid for a particular period.

The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -

  • 1. Job connect
  • 2. Resume Building
  • 3. Mock interview with industry experts
  • 4. Interview questions

The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.

No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.

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