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Artificial Intelligence Course Features

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ARTIFICIAL INTELLIGENCE COURSE FEE IN INDIA

Live Virtual

Instructor Led Live Online

154,000
101,745

  • 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
60,795

  • 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
116,445

  • 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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UPCOMING ARTIFICIAL INTELLIGENCE TRAINING SCHEDULES IN INDIA

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The entire training includes real-world projects and highly valuable case studies.

IABAC® certification provides global recognition of the relevant skills, thereby opening opportunities across the world.

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WHY DATAMITES INSTITUTE FOR ARTIFICIAL INTELLIGENCE ONLINE COURSE

Why DataMites Infographic

SYLLABUS OF AI COURSE IN INDIA

MODULE 1 : DATA SCIENCE COURSE INTRODUCTION 

  • CDS Course Introduction
  • 3 Phase Learning
  • Learning Resources
  • Assessments & Certification Exams
  • DataMites Mobile App
  • Support Channels

MODULE 2 : DATA SCIENCE ESSENTIALS 

  • Introduction to Data Science
  • Evolution of Data Science
  • Data Science Terminologies
  • Data Science vs AI/Machine Learning
  • Data Science vs Analytics

MODULE3 : DATA SCIENCE DEMO 

  • Business Requirement: Use Case
  • Data Preparation
  • Machine learning Model building
  • Prediction with ML model
  • Delivering Business Value

MODULE 4 : ANALYTICS CLASSIFICATION 

  • Types of Analytics
  • Diagnostic Analytics
  • Predictive Analytics
  • Prescriptive Analytics

MODULE 5 : DATA SCIENCE AND RELATED FIELDS 

  • Introduction to AI
  • Introduction to Computer Vision
  • Introduction to Natural Language Processing
  • Introduction to Reinforcement Learning
  • Introduction to GAN
  • Introduction to  Generative Passive Models

MODULE 6 : DATA SCIENCE ROLES & WORKFLOW

  • Data Science Project workflow
  • Roles: Data Engineer, Data Scientist, ML Engineer and MLOps Engineer
  • Data Science Project stages

MODULE 7 : MACHINE LEARNING INTRODUCTION

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

MODULE 8 : DATA SCIENCE INDUSTRY APPLICATIONS 

  • Data Science in Finance and Banking
  • Data Science in Retail
  • Data Science in Health Care
  • Data Science in Logistics and Supply Chain
  • Data Science in Technology Industry
  • Data Science in Manufacturing
  • Data Science in Agriculture

MODULE 1 : PYTHON BASICS 

  • Introduction of python
  • Installation of Python and IDE
  • Python objects
  • Python basic data types
  • Number & Booleans, strings
  • Arithmetic Operators
  • Comparison Operators
  • Assignment Operators
  • Operator’s precedence and associativity

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
  • String object basics and inbuilt methods
  • List: Object, methods, comprehensions
  • Tuple: Object, methods, comprehensions
  • Sets: Object, methods, comprehensions
  • Dictionary: Object, methods, comprehensions

MODULE 4 : PYTHON FUNCTIONS 

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

MODULE 5 : PYTHON NUMPY PACKAGE 

  • NumPy Introduction
  • Array – Data Structure
  • Core Numpy functions
  • Matrix Operations

MODULE 6 : PYTHON PANDAS PACKAGE 

  • Pandas functions
  • Data Frame and Series – Data Structure
  • Data munging with Pandas
  • Imputation and outlier analysis

MODULE 1 : OVERVIEW OF 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
  • Simple Random Sampling
  • Stratified Random Sampling
  • Cluster Random Sampling
  • Systematic Random Sampling
  • Biased Random Sampling Methods
  • 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
  • Z Value / Standard Value
  • Empherical Rule  and Outliers
  • Central Limit Theorem
  • Normality Testing
  • Skewness & Kurtosis
  • Measures Of Distance: Euclidean, Manhattan And MinkowskiDistance

MODULE 4 : HYPOTHESIS TESTING 

  • Hypothesis Testing Introduction
  • P- Value, Confidence Interval
  • Parametric Hypothesis Testing Methods
  • Hypothesis Testing Errors : Type I And Type Ii
  • One Sample T-test
  • Two Sample Independent T-test
  • Two Sample Relation T-test
  • One Way Anova Test

MODULE 5 : CORRELATION AND REGRESSION 

  • Correlation Introduction
  • Direct/Positive Correlation
  • Indirect/Negative Correlation
  • Regression
  • Choosing Right Method

MODULE 1: MACHINE LEARNING INTRODUCTION 

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

MODULE 2: PYTHON NUMPY & PANDAS PACKAGE 

  • NumPy & Pandas functions
  • Array – Data Structure
  • Core Numpy functions
  • Matrix Operations
  • Data Frame and Series – Data Structure
  • Data munging with Pandas
  • Imputation and outlier analysis

MODULE 3: VISUALIZATION WITH PYTHON 

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

MODULE 4: ML ALGO: LINEAR REGRESSSION 

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

MODULE 5: ML ALGO: KNN 

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

MODULE 6: ML ALGO: LOGISTIC REGRESSION 

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

MODULE 7: PRINCIPLE COMPONENT ANALYSIS (PCA) 

  • Building Blocks Of PCA
  • How it works: Finding Principal Components
  • Modeling PCA 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 1: MACHINE LEARNING INTRODUCTION 

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

MODULE 2: ML ALGO: LINEAR REGRESSION 

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

MODULE 3: ML ALGO: LOGISTIC REGRESSION 

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

MODULE 4: ML ALGO: KNN 

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

MODULE 5: ML ALGO: K MEANS CLUSTERING 

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

MODULE 6: PRINCIPLE COMPONENT ANALYSIS (PCA) 

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

MODULE 7: ML ALGO: DECISION TREE 

  • Random Forest Ensemble technique
  • How it works: Bagging Theory
  • Modeling and Evaluation in Python

MODULE 8 : ML ALGO: NAÏVE BAYES 

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

MODULE 9: GRADIENT BOOSTING, XGBOOST 

  • Introduction to Boosting and XGBoost
  • How it works: weak learners' concept
  • Modeling and Evaluation of in Python

MODULE 10: ML ALGO: SUPPORT VECTOR MACHINE  (SVM) 

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

MODULE 11: ARTIFICIAL NEURAL NETWORK (ANN) 

  • Introduction to ANN
  • How It Works: Back prop, Gradient Descent
  • Modeling and Evaluation of ANN in Python

MODULE 12: ADVANCED ML CONCEPTS 

  • Adv Metrics (Roc_Auc, R2, Precision, Recall)
  • K-Fold Cross validation
  • Grid And Randomized Search CV In Sklearn
  • Imbalanced Data Set : Smote Technique
  • Feature Selection Techniques

MODULE 1: TIME SERIES FORECASTING - ARIMA 

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

MODULE 2: FEATURE ENGINEERING 

  • Introduction to Features Engineering
  • Transforming Predictors
  • Feature Selection methods
  • Backward elimination technique
  • Feature importance from ML modeling

MODULE 3: SENTIMENT ANALYSIS 

  • Introduction to Sentiment Analysis
  • Python packages: TextBlob, NLTK
  • Case study: Twitter Live Sentiment Analysis

MODULE 4: REGULAR EXPRESSIONS WITH PYTHON 

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

MODULE 5: ML MODEL DEPLOYMENT WITH FLASK 

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

MODULE 6: ADVANCED DATA ANALYSIS WITH MS EXCEL 

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

MODULE 7: AWS CLOUD FOR DATA SCIENCE

  • Introduction of cloud
  • Difference between GCC, Azure,AWS
  • AWS Service ( EC2 and S3 service)
  • AWS Service (AMI), AWS Service (RDS)
  • AWS Service (IAM), AWS (Athena service)
  • AWS (EMR), AWS, AWS (Redshift)
  • ML Modeling with AWS Sage Maker 

MODULE 8: AZURE FOR DATA SCIENCE 

  • Introduction to AZURE ML studio
  • Data Pipeline and ML modeling with Azure
  • MODULE 1: DATABASE INTRODUCTION 

    • DATABASE Overview
    • Key concepts of database management
    • CRUD Operations
    • Relational Database Management System
    • RDBMS vs No-SQL (Document DB)

    MODULE 2: SQL BASICS 

    • Introduction to Databases
    • Introduction to SQL
    • SQL Commands
    • MY SQL  workbench installation
    • Comments • import and export dataset

    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

    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
    • MongoDB data management

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
  • Copying existing repo
  • Git user and remote node
  • Git Status and rebase
  • Review Repo History
  • GitHub Cloud Remote Repo

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

MODULE 5: UNDOING CHANGES 

  • Editing Commits
  • Commit command Amend flag
  • Git reset and revert

MODULE 6: GIT WITH GITHUB AND BITBUCKET 

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

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
  • Hands-on Map Reduce task

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
  • Working with Spark SQL Query Language

MODULE 5: MACHINE LEARNING WITH SPARK ML 

  • Introduction to MLlib Various ML algorithms supported by MLib
  • ML model with Spark ML
  • Linear regression
  • logistic regression
  • Random forest

MODULE 6: KAFKA and Spark 

  • Kafka architecture
  • Kafka workflow
  • Configuring Kafka cluster
  • Operations

MODULE 1: BUSINESS INTELLIGENCE INTRODUCTION 

  • What Is Business Intelligence (BI)?
  • What Bi Is The Core Of Business Decisions?
  • BI Evolution
  • Business Intelligence Vs Business Analytics
  • Data Driven Decisions With Bi Tools
  • The Crisp-Dm Methodology

MODULE 2: BI WITH TABLEAU: INTRODUCTION 

  • The Tableau Interface
  • Tableau Workbook, Sheets And Dashboards
  • Filter Shelf, Rows And Columns
  • Dimensions And Measures
  • Distributing And Publishing

MODULE 3 : TABLEAU: CONNECTING TO DATA SOURCE 

  • Connecting To Data File , Database Servers
  • Managing Fields
  • Managing Extracts
  • Saving And Publishing Data Sources
  • Data Prep With Text And Excel Files
  • Join Types With Union
  • Cross-Database Joins
  • Data Blending
  • Connecting To Pdfs

MODULE 4 : TABLEAU : BUSINESS INSIGHTS 

  • Getting Started With Visual Analytics
  • Drill Down And Hierarchies
  • Sorting & Grouping
  • Creating And Working Sets
  • Using The Filter Shelf
  • Interactive Filters
  • Parameters
  • The Formatting Pane
  • Trend Lines & Reference Lines
  • Forecasting
  • Clustering

MODULE 5 : DASHBOARDS, STORIES AND PAGES 

  • Dashboards And Stories Introduction
  • Building A Dashboard
  • Dashboard Objects
  • Dashboard Formatting
  • Dashboard Interactivity Using Actions
  • Story Points
  • Animation With Pages

MODULE 6 : BI WITH POWER-BI 

  • Power BI basics
  • Basics Visualizations
  • Business Insights with Power BI

MODULE 1: ARTIFICIAL INTELLIGENCE OVERVIEW 

  • Evolution Of Human Intelligence
  • What Is Artificial Intelligence?
  • History Of Artificial Intelligence
  • Why Artificial Intelligence Now?
  • Ai Terminologies
  • 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

MODULE 3: TENSORFLOW FOUNDATION 

  • TensorFlow Installation and setup
  • 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
  • Language Modeling
  • 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: NEURAL NETWORKS 

  • Structure of neural networks
  • Neural network - core concepts
  • Feed forward algorithm
  • Backpropagation
  • Building neural network from scratch using Numpy

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 - CNN 

  • Convolutional neural networks (CNNs)
  • Introduction
  • CNNs with Keras
  • Transfer learning in CNN
  • Style transfer
  • Flowers dataset with tf2.X
  • Examining x-ray with CNN model

MODULE 4 : RECURRENT NEURAL NETWORK 

  • RNN introduction
  • Sequences with RNNs
  • Long short-term memory networks
  • LSTM RNNs and GRU
  • Examples of RNN applications

MODULE 5: NATURAL LANGUAGE PROCESSING (NLP) 

  • Natural language processing
  • Introduction
  • NLP with RNNs
  • Creating model
  • Transformers and BERT
  • State of art NLP and projects

MODULE 6: REINFORCEMENT LEARNING 

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

MODULE 7: DEEP REINFORCEMENT LEARNING 

  • Architectures of deep Q learning
  • Deep Q learning
  • Policy gradient methods

MODULE 8: GENERATIVE ADVERSARIAL NETWORK (GAN) 

  • Gan introduction
  • Core concepts of GAN
  • Building GAN model with TensorFlow 2.X
  • GAN applications

MODULE 9: DEPLOYING DL MODELS IN THE CLOUD (AWS) 

  • Amazon web services (AWS)
  • AWS SageMaker Overview
  • Sage Makers from Data pipeline to deployments
  • Deploying deep learning models WS Sage maker

OFFERED ARTIFICIAL INTELLIGENCE COURSES IN INDIA

ARTIFICIAL INTELLIGENCE TRAINING REVIEWS

ABOUT ARTIFICIAL INTELLIGENCE TRAINING IN INDIA

An Artificial Intelligence course in India offers the opportunity to delve into a rapidly growing field, equipping students with cutting-edge skills in machine learning, data analysis, and innovative problem-solving. According to a BlueWeave Consulting report, the market size for artificial intelligence (AI) in India was valued at approximately $672.11 million in 2022. It is anticipated to expand at a compound annual growth rate (CAGR) of 32.26% from 2023 to 2029, culminating in a market value of around $3,966.51 million by the end of 2029.

DataMites provides in-depth offline courses in artificial intelligence in India, complete with hands-on internships and support for job placements. These courses are designed to cater to the increasing need for AI expertise in the rapidly growing industry.

DataMites addresses the rising need for AI skills by providing top-notch artificial intelligence training in India. Our course for Artificial Intelligence Engineers is designed for both beginners and intermediate students, integrating elements of AI Expert and Certified Data Scientist programs. This career-oriented curriculum includes fundamental topics such as statistics, mathematics, Python programming, and comprehensive machine learning.

DataMites Three-Step Innovative Approach to Learning Artificial Intelligence in India:

Phase 1 - Pre-Course Self-Study: Our program starts with self-guided learning using premium videos to establish a solid base in the fundamentals of Artificial Intelligence.

Phase 2 - Engaging Learning Experience: Students can choose either live online or offline artificial intelligence courses in India. This interactive phase involves 300 hours of instruction spread over three months, which includes a detailed curriculum, practical projects, and mentorship from experienced trainers. DataMites offers its artificial intelligence course in multiple locations, including Bangalore, Chennai, Hyderabad, Pune, Mumbai, Ahmedabad, Bhubaneswar, Nagpur, Kolkata, and Delhi.

Phase 3 - Internship and Job Placement Support: This stage provides practical experience through 10 Capstone Projects and a client project, along with a valuable certification in an artificial intelligence internship based in India.

In our artificial intelligence training in India, the Placement Assistance Team (PAT) offers extensive career counseling and support, facilitating a seamless entry into AI-related careers. This training, which includes placement services, emphasizes practical skills to ensure you are thoroughly prepared for a career in artificial intelligence.

Other Artificial Intelligence Certification in India 

DataMites provides an array of high-quality Artificial Intelligence certifications in India, each designed to meet diverse professional requirements. The offerings include:

Artificial Intelligence for Managers: This program equips managers with AI insights, emphasizing strategic execution and leadership in AI initiatives. Tailored for decision-makers, it aims to seamlessly incorporate AI into business operations.

Artificial Intelligence Expert: Designed for both newcomers and those at an intermediate level in data science. This course offers a career-oriented introduction to data science, covering essential topics such as statistics, mathematics, Python programming, and comprehensive machine learning knowledge.

Certified NLP Expert: This course delves into the understanding of human language by machines, specializing in Natural Language Processing. It's perfect for individuals interested in the intersection of AI, linguistics, and communication.

Artificial Intelligence Foundation: A beginner-level course that provides a broad understanding of the basic concepts and tenets of AI, laying a strong foundation for advanced studies in the area.

DataMites Artificial Intelligence Course Syllabus in India

DataMites provides two premier programs in Artificial Intelligence: the AI Expert and AI Engineer courses.

The AI Expert Course in India at DataMites equips students with a comprehensive understanding of advanced topics like neural networks, deep learning, natural language processing, and reinforcement learning, ensuring proficiency in the latest AI technologies.

Module 1: Neural Networks

  1. Structure of neural networks

  2. Core concepts of neural networks

  3. Feedforward algorithm

  4. Backpropagation

  5. Building neural networks from scratch using Numpy.

Module 2: Implementing Deep Neural Networks

  1. Introduction to neural networks with tf2.X

  2. Creating a simple deep learning model in Keras (tf2.X)

  3. Building a neural network model in TF2.0 for the MNIST dataset

Module 3: Deep Computer Vision - Cnn

  1. Introduction to Convolutional Neural Networks (CNNs)

  2. CNNs with Keras

  3. Transfer learning in CNN

  4. Style transfer

  5. Working with the Flowers dataset using tf2.X

  6. Examining X-ray images with a CNN model

Module 4: Natural Language Processing (NLP)

  1. Introduction to Natural Language Processing (NLP)

  2. NLP with Recurrent Neural Networks (RNNs)

  3. Creating NLP models

  4. Introduction to Transformers and BERT

  5. NLP and project examples

Module 5: Recurrent Neural Network

  1. Introduction to Recurrent Neural Networks (RNNs)

  2. Working with sequences using RNNs

  3. Long Short-Term Memory Networks (LSTM) and GRU

  4. Real-world examples of RNN applications

Module 6: Deep Reinforcement Learning

  1. Architectures of Deep Q Learning

  2. Deep Q Learning

  3. Policy gradient methods

Module 7: Generative Adversarial Network (Gan)

  1. Introduction to Generative Adversarial Networks (GANs)

  2. Core concepts of GAN

  3. Building GAN models with TensorFlow 2.X

  4. Real-world GAN applications

Module 8: Deploying Dl Models In The Cloud (Aws)

  1. Introduction to Amazon Web Services (AWS)

  2. Overview of AWS SageMaker

  3. From data pipeline to model deployments with SageMaker

  4. Deploying deep learning models with AWS SageMaker

DataMites Artificial Intelligence Engineer Training in India is recognized as a leading choice for AI education in the industry. The curriculum is regularly updated to keep pace with the constantly changing industry requirements, guaranteeing that students acquire the latest knowledge and skills in AI.

Our Artificial Intelligence Engineer Course combines elements from both the AI Expert and Certified Data Scientist (CDS) programs, providing a thorough education in both artificial intelligence and data science. This course includes an extensive array of topics from the CDS syllabus, such as:

  1. Python Foundation

  2. Data Science Foundations

  3. Machine Learning Expert

  4. Advanced-Data Science

  5. Version Control with Git

  6. Big Data Foundation

  7. Certified BI Analyst

  8. Database: SQL and MongoDB

  9. Artificial Intelligence Foundation

The subjects covered in the CDS course lay a solid groundwork in data science, which is effectively incorporated into the AI Engineer Course. This comprehensive strategy prepares our students with the essential knowledge and skills to thrive in the ever-evolving field of artificial intelligence.

DataMites Artificial Intelligence Course Tools in India

In the DataMites Artificial Intelligence courses in India, we encompass a broad spectrum of AI tools to provide you with the required skills and proficiency. The tools covered in the course include:

  1. Anaconda
  2. Python
  3. Apache Pyspark
  4. Git
  5. Hadoop
  6. MySQL
  7. MongoDB
  8. Amazon SageMaker
  9. Google Bert
  10. Google Colab
  11. Advanced Excel
  12. Scikit Learn
  13. Azure Machine Learning
  14. Flask
  15. Apache Kafka
  16. Power BI
  17. GitHub
  18. Numpy
  19. TensorFlow
  20. Pandas
  21. Tableau
  22. Atlassian BitBucket
  23. Natural Language Toolkit
  24. PyCharm

Why DataMites for Artificial Intelligence Training in India?

Distinguished Teaching Staff: Directed by Ashok Veda, a world-renowned expert in Artificial Intelligence with a vast experience spanning 19 years.

Globally Acknowledged Certifications: Our programs are endorsed by renowned organizations like IABAC and NASSCOM FutureSkills.

Advanced Educational Materials: DataMites offer the latest in teaching materials and instructional methodologies.

Practical Application Opportunities: Students engage in projects that mirror the complexities of real-world scenarios.

Adaptable Learning Mode: DataMites provides training in both online and offline artificial intelligence courses in India for better learning preferences.

The significance of artificial intelligence course with internship in India

An Artificial Intelligence course with an internship in India offers practical experience, bridging the gap between academic concepts and real-world application. It enhances employability by providing hands-on skills and industry exposure. Additionally, it fosters innovation and problem-solving abilities, crucial for thriving in India's rapidly growing tech sector.

At DataMites, the artificial intelligence courses in India include internships, allowing students to not just acquire knowledge but also apply it in real-world settings. This combination of theoretical learning and hands-on experience is crucial in developing comprehensive AI professionals, providing them with a unique edge in their career paths.

The significance of artificial intelligence course with placement program in India

An Artificial Intelligence course with a placement program in India provides vital industry-relevant skills, enhancing job readiness. It bridges the gap between academic learning and professional requirements. This integration of education and career opportunities is crucial for launching successful careers in India's burgeoning AI sector.

DataMites acknowledges the significance of integrating Artificial Intelligence courses with placement programs in India. By adopting this strategy in our data science job-ready program, we ensure that our students gain not only AI education but also receive effective guidance towards successful careers in the industry.

India, a country with a rich history and diverse culture, has become a global hub for information technology (IT) and innovation. The Indian IT sector is characterized by rapid growth and technological advancements, making it a key player in the global tech landscape. This boom in IT is propelled by several factors, including a large pool of skilled professionals, cost-effectiveness, and supportive government policies.

Leading the charge in India's IT revolution are some top companies renowned for their cutting-edge work in artificial intelligence (AI) and other tech domains. IT Companies in India like Infosys, TCS (Tata Consultancy Services), Wipro, and HCL Technologies are at the forefront, offering a plethora of opportunities for AI engineers. These companies are known for their innovative solutions and are continually on the lookout for talented individuals who can contribute to their AI-driven projects.

The demand for AI engineers in these companies reflects the growing importance of AI in solving complex problems and creating new products and services. From healthcare and finance to e-commerce and education, AI is transforming how industries operate, and these Indian IT giants are leading this transformation. The combination of a booming IT sector and the surge in demand for AI expertise makes India an exciting and dynamic place for technology professionals.

The career landscape for AI professionals in India is exceptionally promising, given the country's rapid technological advancement and growing focus on AI-driven solutions across various industries. AI careers in India span a wide range of roles, including data scientists, machine learning engineers, AI researchers, and AI project managers. These roles are in high demand in sectors like IT, healthcare, finance, e-commerce, and automotive, among others.

Salaries for AI professionals in India are competitive and vary based on experience, skill level, and the specific industry. Entry-level AI engineers can expect to earn between INR 3.0 lakhs per annum according to Ambition Box, while the Senior AI engineers, especially those with specialized skills in machine learning, deep learning, and data science, can command salaries upwards of INR 17,89,606 per year according to a Glassdoor report, and even higher in some cases. This lucrative pay scale reflects the high value and demand for AI expertise in the country's growing tech ecosystem.

Enrol in DataMites Artificial Intelligence Training in India and embark on a journey towards success in this dynamic field. Our institute is globally recognized for offering a variety of courses in key areas such as Artificial Intelligence, Data Science, Data Analytics, Machine Learning, and Blockchain. This program is designed to equip you with the skills and knowledge needed to excel in these cutting-edge technologies.

DESCRIPTION OF ARTIFICIAL INTELLIGENCE COURSE IN INDIA

Artificial Intelligence is a branch of Computer Science which talks about incorporating the reasoning and decision making capabilities demonstrated by humans, into a machine, which makes it possible for the machine to exercise the critical tasks which require human intervention.

The Artificial Intelligence Engineer course offered by DataMites consists of a bundle of different courses- Artificial Intelligence Foundation, Machine Learning, Tensorflow 2.X Platform, Core Learning Algorithms, Neural Networks, Implementing Deep Neural Networks, Reinforcement Learning, Natural Language Processing, etc. 

The Artificial Intelligence Engineer is the most comprehensive course with the following features:- 

  • Dual Certification- IABAC and IBM (Best in class industry certification)

  • 6 months of live online training.

  • Training by industry experts.

  • Internship Opportunities(10 Capstone Projects and 1 Client Project)

Machine Learning is a branch of Artificial Intelligence, which concerns the ability of machines to learn from experience and subsequently improve themselves, without being influenced by another person.

Deep Learning is a part of Artificial Intelligence and Machine Learning. To be precise, when the data is huge in numbers, Machine Learning doesn’t hold good, as they are incapable of going deep into the data sets. Deep Learning helps to address this problem.  The structure of Deep Learning comprises Artificial Neural Networks which resemble the neuron structure in the human brain. These networks have different layers and are capable enough to pierce inside the large data set to retrieve the relevant information.

The prerequisites to pursue an  Al Engineer course are:

Educational Qualifications

  •  Graduation/PG in Computer Science, IT, Statistics
  •  Certification in Data Science, Machine Learning, Deep Learning, etc.

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

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

  • Analytical Skills

  • Problem Solving 

  • Communication Skills

  • Business Acumen

Python is the most preferred among programming languages in the field of Data Science and Artificial Intelligence. As far as Data Scientist is concerned Python is the most effective programming language, with a lot of libraries available. Python can be deployed at every phase of data science functions. It is beneficial in capturing data and importing it into SQL. Python can also be used to create data sets. 

The Artificial Intelligence course offered by DataMites comprises a topic on Python Programming language. Having a basic understanding of Python is an added advantage for the Artificial Intelligence course.

Machine Learning and Artificial Intelligence are two inter-related topics. The Artificial intelligence course provided by DataMites comprises Machine Learning as a part of its syllabus. However, a basic knowledge of Machine Learning would be an advantage while joining the course.

Yes. The Artificial Intelligence course provided by DataMites covers a topic on Python. It includes concepts such as Building ML Classification Models with Python, Building ML Regression Models with Python, CIFAR-10 classification with Python, Transfer Learning In Python, RNNS In Python.

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

P.G degree is not a mandatory requirement to pursue an Artificial Intelligence certification. However, a sound knowledge of Technology, Engineering, and Management domains will be an added advantage.

Artificial Intelligence is present everywhere nowadays and is used across functions like Finance, Healthcare, Education, Manufacturing, Retail, Customer Service, etc. Therefore learning Artificial Intelligence will help to increase the chances of your employability in various sectors. AI is also an indispensable factor, for the reason that most of the data today are stored digitally. The potential of AI to be incorporated into data helps in making the right decisions.

The Artificial Intelligence course in India offered by DataMites helps to give you a clear picture of the role of AI in decision making and the problem-solving process.

This Artificial Intelligence course enables you to:-

  • Understand AI and its relevance in bringing in change in the current industrial scenario.

  • Learn the terminologies that are used in the AI domain.

  • Gain practical knowledge of employing AI and related disciplines in solving complex real-world problems.

  • Make decision making easy.

India is known for lots of business opportunities and large corporate houses adorning the city. This, in turn, contributes to new employment opportunities being created. 

Learning the Artificial Intelligence course in India helps you to leverage the available opportunities and also prepares you for the challenges. Artificial Intelligence is a discipline that is influencing the present in a big way and is expected to grow in the future. Therefore by learning AI you are at the advantage of remaining well equipped in advance to cope with the changing times.

DataMites is India that offers the most comprehensive Artificial Intelligence course that is aligned with the state of art industry best practices in the Artificial Intelligence domain.

India has a lot of business opportunities with large corporates gracing the city. The career opportunities in Artificial Intelligence are booming and India is no exception.

DataMites is India that provides the most comprehensive Artificial Intelligence Engineer course with the following features.

  • Dual Certification- IABAC and IBM(Best in class industry certification)

  • Experienced Trainers

  • Industry aligned courses

  • Internship Opportunities

  • Job assistance

DataMites caters to graduates and professionals equally. Therefore, DataMites is the best choice for anyone who wishes to become an Artificial Intelligence Engineer in India.

India, in India, is known for lots of business opportunities. It consists of many large companies, business houses, with large amounts of transactions happening every day, as a result of which there is an equally large amount of data generated daily. Also, India. is known for many recognized universities. Learning Artificial Intelligence in India will be a great opportunity for students as well as professionals.

DataMites is India that provides the most comprehensive Artificial Intelligence course that is designed as per the current industry requirements. Also, the Artificial Intelligence course provided by DataMites in India is dually certified in collaboration with IABAC and IBM.

On completing the Artificial Intelligence course DataMites in India you will be eligible for the following job roles:-

  • Artificial Intelligence Engineer

  • Data Scientist

  • Machine Learning Expert

  • Analytics Manager

The market for Artificial Intelligence in India is booming and is expected to grow in the future. As AI requires the mastering of various disciplines and there are only a few who are good at all of them, the one who canto the disciplines is at a greater advantage. Career Opportunities in AI are plenty but there is a shortage of skilled AI professionals, therefore there is also a rising demand for the same. Some of the top industries in India for AI are- Banking and Finance,  Information and Communication, Administration, and Support Services.

According to glassdoor.com the average salary of an Artificial Intelligence Engineer in India is Rs 753000 per year.

India has a good number of small, medium, and large corporations. The opportunity in Artificial Intelligence in the UK is also plenty. As AI has shown us a way to tackle real-world complexities, the need to incorporate AI into various functions is equally important. All the present-day organizations are well aware of this and have acknowledged this to a great extent.  In simple words, most companies nowadays have found a better way of tackling their day- to day problems with the help of AI. 

Every company in India(Be it Small, Medium, and Large enterprises) requires AI professionals as all of them work on their data and requires some or the other AI expertise to be deployed into the tasks.

Artificial Intelligence, Machine, and Data Science contribute to one another in one or the other way.  Python and R are the two programming languages that are used in the data science process. Some of the reasons, for python being the most preferred programming language in comparison to R:-

  • Easy to learn: Python is easier to understand and master, in comparison to R 

  • Flexible: The flexibility offered by Python offers is better when compared to the R programming language.

  • Availability of libraries: Python has a wide range of libraries available, such as pandas, scikit-learn, etc. This makes it easier in handling machine learning projects.

  • Data visualization: By using matplotlib in Python, you can do the plotting of complex data representations into 2D plots. Data visualization is a significant process in the job of a data scientist. Python can be used for Data Visualisation. 

However as far as Artificial Intelligence is concerned, learning both Python and R will be advantageous.

The instructors at DataMites institute are industry experts who have a good number of years of experience in the field of Artificial Intelligence.

Enrolling for online training online is very simple. The payment can be done using your debit/credit card that includes Visa Card, MasterCard; American Express, or PayPal. You will receive the receipt after the payment is successful. You can get in touch with our educational counsellor for more information.

DataMites conducts classes for Artificial Intelligence courses both during Weekdays and Weekends. You can opt between the two according to your convenience.

DataMites conducts both morning and evening classes for Artificial Intelligence courses in India. You can opt between the two as per your convenience.

Yes. DataMites provides an online lab facility called Pro Lab. You can log in with a username to use this facility.

Yes, DataMites has partnered with many AI companies and provides live Artificial Intelligence projects to work on which helps the candidate to get exposure to the real-world working environment. DataMites provides 10 capstones and 1 client project as part of the Artificial Intelligence course.

The DataMites Placement Assistance Team(PAT) helps the candidates to have an easy start in his/her career. The team offers services like Resume Building, Interview Preparation. The team will assist you in the following areas;-

Project Mentoring- 100 hrs Live mentoring in industry projects.

Interview Preparations- Mock Interview sessions.

Resume Support- Personal guidance in resume creation by professionals.

Doubt clearing sessions- Live doubt clearing sessions on 

Job updates- Interview connects.

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FAQ’S OF ARTIFICIAL INTELLIGENCE TRAINING IN INDIA

The training provided by DataMites for Artificial Intelligence in India is mainly through three modes, namely, Live Virtual/Online, Classroom, and Self Learning.

DataMites is a global institute that offers comprehensive courses in Artificial Intelligence. The syllabus is designed in tune with the current industry trends and helps to cater to the needs of fresh AI aspirants and experienced professionals. The Artificial Intelligence course offered by DataMites is unique in the following ways.

DataMites offers an Artificial Intelligence course in India 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/-.

DataMites is India that offers dual certifications in collaboration with IABAC and IBM. IABAC is a global body, which offers certifications in Business Analytics and Data Science. IABAC is founded on the principles of the EDISON Data Science Framework (EDSF). IBM provides the best in class industry certifications. DataMites provides a range of certifications in Data Science, Machine Learning, Artificial Intelligence. All the data science certifications offered by DataMites are structured based on the industry trends.

DataMites in India provide training sessions for the Artificial Intelligence course in three different modes- Live Virtual/Online, Classroom, and Self-learning.

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 India 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 India 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 is India, offers quality training sessions in Artificial Intelligence, Machine Learning, etc. The Artificial Intelligence courses provided by DataMites in India 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 India in three different modes. The Live Virtual/Online and Classroom training is offered at Rs 99000/-, and the Self Learning mode is offered at Rs 69000/-.

The registrations canceled 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 India 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 concepts such as Building ML Classification Models with Python, Building ML Regression Models with Python, CIFAR-10 classification with Python, Transfer Learning In Python, RNNS In Python. 

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 India includes 10 capstone projects and 1 client project.

The mode of training offered by DataMites in India is primarily online. However, classroom training can be made available in India,  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 India is exclusively designed in tune with the current industry trends. The following makes DataMites unique from others:-

  • Dual Certification- IABAC and IBM(Best in class industry certification)

  • 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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