X

Stay Updated!

These batches are going to start very soon.

We will send you the emails occassionally only for sharing important information with you.

Training Courses

Python


DURATION

45 Days

PROJECT

Demo

Prerequisite

Basic knowledge of concepts like Variables, Loops, Control Statements etc.

Contents

  1. Python Training Overview
    • 1.1 What are the Python Course Pre-requisites
    • 1.2 Objectives of the Course
    • 1.3 Who should do the course
    • 1.4 Python Training Course Duration
  2. Python Course Content
    • 2.1 Core Python
      • 2.1.1 Introduction to Script
      • 2.1.2 Introduction to Python
      • 2.1.3 Different Modes in PYTHON
      • 2.1.4 PYTHON NEW IDEs
      • 2.1.5 Variables in Python
      • 2.1.6 String Handling
      • 2.1.7 Python Operators and Operands
      • 2.1.8 Python Conditional Statements
      • 2.1.9 Python LOOPS
      • 2.1.10 Learning Python Strings
      • 2.1.11 Sequence or Collections in PYTHON
      • 2.1.12 Python Lists
      • 2.1.13 Python TUPLE
      • 2.1.14 Python Sets
      • 2.1.15 Python Dictionary
      • 2.1.16 Python Functions
    • 2.2 Advanced Python
      • 2.2.1 Python Modules
      • 2.2.2 Packages in Python
      • 2.2.3 Python Date and Time
      • 2.2.4 File Handling
      • 2.2.5 Python OS Module
      • 2.2.6 Python Exception Handling
      • 2.2.7 More Advanced PYTHON
      • 2.2.8 Python Class and Objects
      • 2.2.9 Python Regular Expressions
      • 2.2.10 Python XML Parser
      • 2.2.11 Python-Data Base Communication
      • 2.2.12 Multi-Threading
      • 2.2.13 Web Scrapping
      • 2.2.14 Unit Testing with PyUnit
      • 2.2.15 Introduction to Python Web Frameworks
      • 2.2.16 GUI Programming-Tkinter
      • 2.2.17 Data Analytics
      • 2.2.18 Introduction to Machine Learning with PYTHON
      • 2.2.19 Data Science
      • 2.2.20 Internet of Things

AI-ML


DURATION

4-6 months

PROJECT

1 project

Prerequisite

Basic understanding of computers and programming concepts

Contents

  1. AI & ML Training Overview
    • 1.1 What are AI & ML Course Pre-requisites
    • 1.2 Objectives of the AI & ML Course
    • 1.3 Who should do the course
    • 1.4 AI & ML Training Course Duration
  2. AI & ML Course Content
    • 2.1 Artificial Intelligence Fundamentals
      • 2.1.1 Introduction to Artificial Intelligence
      • 2.1.2 History and Evolution of AI
      • 2.1.3 AI Applications and Use Cases
      • 2.1.4 Types of AI (Narrow, General, Super AI)
      • 2.1.5 Intelligent Agents
      • 2.1.6 Search Algorithms (BFS, DFS)
      • 2.1.7 Heuristic Search Techniques
      • 2.1.8 Knowledge Representation
      • 2.1.9 Expert Systems
      • 2.1.10 Ethics and Challenges in AI
    • 2.2 Machine Learning Fundamentals
      • 2.2.1 Introduction to Machine Learning
      • 2.2.2 Types of Machine Learning
      • 2.2.3 Supervised Learning
      • 2.2.4 Unsupervised Learning
      • 2.2.5 Reinforcement Learning
      • 2.2.6 ML Workflow and Model Lifecycle
      • 2.2.7 Data Collection and Preprocessing
      • 2.2.8 Feature Engineering
      • 2.2.9 Model Training and Evaluation
    • 2.3 Machine Learning Algorithms
      • 2.3.1 Linear Regression
      • 2.3.2 Logistic Regression
      • 2.3.3 K-Nearest Neighbors (KNN)
      • 2.3.4 Decision Trees
      • 2.3.5 Random Forest
      • 2.3.6 Support Vector Machines (SVM)
      • 2.3.7 Naive Bayes
      • 2.3.8 Clustering Algorithms (K-Means, Hierarchical)
      • 2.3.9 Dimensionality Reduction (PCA)
    • 2.4 Deep Learning
      • 2.4.1 Introduction to Deep Learning
      • 2.4.2 Neural Networks Basics
      • 2.4.3 Activation Functions
      • 2.4.4 Forward & Backpropagation
      • 2.4.5 Convolutional Neural Networks (CNN)
      • 2.4.6 Recurrent Neural Networks (RNN)
      • 2.4.7 LSTM & GRU
      • 2.4.8 Deep Learning Frameworks Overview
    • 2.5 Natural Language Processing (NLP)
      • 2.5.1 Introduction to NLP
      • 2.5.2 Text Preprocessing
      • 2.5.3 Tokenization & Lemmatization
      • 2.5.4 Bag of Words & TF-IDF
      • 2.5.5 Sentiment Analysis
      • 2.5.6 Chatbots & Language Models
    • 2.6 Computer Vision
      • 2.6.1 Introduction to Computer Vision
      • 2.6.2 Image Processing Basics
      • 2.6.3 Image Classification
      • 2.6.4 Object Detection
      • 2.6.5 Face Recognition
    • 2.7 AI & ML with Python
      • 2.7.1 Python for AI & ML
      • 2.7.2 NumPy and Pandas
      • 2.7.3 Matplotlib and Seaborn
      • 2.7.4 Scikit-learn
      • 2.7.5 Model Deployment Basics
    • 2.8 Projects & Case Studies
      • 2.8.1 Machine Learning Mini Projects
      • 2.8.2 Real-world AI Case Studies
      • 2.8.3 Capstone Project
      • 2.8.4 Interview Preparation & Career Guidance

IoT


DURATION

3 to 5 Months

PROJECT

1 Project

Prerequisite

Basic knowledge of computers and internet concepts

Contents

  1. IoT (Internet of Things) Training Overview
    • 1.1 What are IoT Course Pre-requisites
    • 1.2 Objectives of the IoT Course
    • 1.3 Who should do the course
    • 1.4 IoT Training Course Duration
  2. IoT Course Content
    • 2.1 Introduction to Internet of Things
      • 2.1.1 What is IoT?
      • 2.1.2 Evolution and Importance of IoT
      • 2.1.3 IoT Architecture
      • 2.1.4 IoT Ecosystem and Components
      • 2.1.5 IoT Applications and Use Cases
    • 2.2 Hardware Fundamentals
      • 2.2.1 Microcontrollers vs Microprocessors
      • 2.2.2 Arduino Overview
      • 2.2.3 Raspberry Pi Overview
      • 2.2.4 Sensors and Actuators
      • 2.2.5 Breadboard and Circuit Basics
    • 2.3 Programming for IoT
      • 2.3.1 Embedded C Basics
      • 2.3.2 Python for IoT
      • 2.3.3 Arduino Programming
      • 2.3.4 GPIO Programming
    • 2.4 Communication Protocols
      • 2.4.1 IoT Communication Models
      • 2.4.2 HTTP and REST APIs
      • 2.4.3 MQTT Protocol
      • 2.4.4 CoAP Protocol
      • 2.4.5 Bluetooth, ZigBee, Wi-Fi
    • 2.5 IoT Networking
      • 2.5.1 IP Addressing
      • 2.5.2 TCP/IP Basics
      • 2.5.3 Cloud Connectivity
      • 2.5.4 Edge Computing
    • 2.6 Cloud Platforms for IoT
      • 2.6.1 Introduction to IoT Cloud Platforms
      • 2.6.2 AWS IoT Core Basics
      • 2.6.3 Azure IoT Hub Basics
      • 2.6.4 Google Cloud IoT Overview
      • 2.6.5 Data Storage and Visualization
    • 2.7 IoT Security
      • 2.7.1 IoT Security Challenges
      • 2.7.2 Device Authentication
      • 2.7.3 Data Encryption
      • 2.7.4 Secure Communication
      • 2.7.5 Best Security Practices
    • 2.8 Industrial IoT (IIoT)
      • 2.8.1 Introduction to IIoT
      • 2.8.2 Smart Manufacturing
      • 2.8.3 Smart Grid Systems
      • 2.8.4 Predictive Maintenance
    • 2.9 IoT Data Analytics
      • 2.9.1 IoT Data Collection
      • 2.9.2 Real-time Data Processing
      • 2.9.3 IoT with Big Data
      • 2.9.4 IoT with Machine Learning
    • 2.10 Projects & Case Studies
      • 2.10.1 Smart Home Automation Project
      • 2.10.2 Smart Weather Monitoring System
      • 2.10.3 Industrial IoT Mini Project
      • 2.10.4 Capstone Project & Deployment

React Native


DURATION

3 to 4 Months

PROJECT

1 Project

Prerequisite

Basic knowledge of JavaScript, Understanding of HTML & CSS basics

Contents

  1. React Native Training Overview
    • 1.1 What are React Native Course Pre-requisites
    • 1.2 Objectives of the React Native Course
    • 1.3 Who should do the course
    • 1.4 React Native Training Course Duration
  2. React Native Course Content
    • 2.1 Mobile App Development Fundamentals
      • 2.1.1 Introduction to Mobile Applications
      • 2.1.2 Native vs Hybrid Apps
      • 2.1.3 Introduction to React Native
      • 2.1.4 React Native Architecture
      • 2.1.5 Setting up Development Environment
    • 2.2 JavaScript & React Basics
      • 2.2.1 JavaScript ES6+ Concepts
      • 2.2.2 Introduction to React
      • 2.2.3 JSX and Components
      • 2.2.4 Props and State
      • 2.2.5 Functional Components & Hooks
    • 2.3 Core React Native Components
      • 2.3.1 View, Text, Image
      • 2.3.2 ScrollView & FlatList
      • 2.3.3 TextInput & Button
      • 2.3.4 StyleSheet & Flexbox
      • 2.3.5 Platform-specific Components
    • 2.4 Navigation & Routing
      • 2.4.1 React Navigation Setup
      • 2.4.2 Stack Navigation
      • 2.4.3 Tab Navigation
      • 2.4.4 Drawer Navigation
    • 2.5 State Management
      • 2.5.1 Local State Management
      • 2.5.2 Context API
      • 2.5.3 Redux Basics
      • 2.5.4 Redux Toolkit
    • 2.6 API & Backend Integration
      • 2.6.1 REST API Concepts
      • 2.6.2 Fetch & Axios
      • 2.6.3 Authentication & Authorization
      • 2.6.4 Handling Async Data
    • 2.7 Native Device Features
      • 2.7.1 Camera Integration
      • 2.7.2 Image Picker
      • 2.7.3 Location & Maps
      • 2.7.4 Push Notifications
    • 2.8 Performance & Optimization
      • 2.8.1 Performance Best Practices
      • 2.8.2 Debugging Tools
      • 2.8.3 Error Handling
      • 2.8.4 App Security Basics
    • 2.9 App Build & Deployment
      • 2.9.1 Android Build Process
      • 2.9.2 iOS Build Process
      • 2.9.3 App Store & Play Store Guidelines
      • 2.9.4 Publishing Mobile Apps
    • 2.10 Projects & Case Studies
      • 2.10.1 To-Do Mobile App
      • 2.10.2 E-commerce Mobile App
      • 2.10.3 Social Media App Features
      • 2.10.4 Capstone Project

Flutter


DURATION

3 to 4 Months

PROJECT

1 Project

Prerequisite

Basic understanding of programming concepts, Familiarity with mobile apps usage.

Contents

  1. Flutter Training Overview
    • 1.1 What are Flutter Course Pre-requisites
    • 1.2 Objectives of the Flutter Course
    • 1.3 Who should do the course
    • 1.4 Flutter Training Course Duration
  2. Flutter Course Content
    • 2.1 Mobile App Development Basics
      • 2.1.1 Introduction to Mobile Applications
      • 2.1.2 Native vs Hybrid App Development
      • 2.1.3 Introduction to Flutter
      • 2.1.4 Flutter Architecture
      • 2.1.5 Flutter SDK & Environment Setup
    • 2.2 Dart Programming Language
      • 2.2.1 Introduction to Dart
      • 2.2.2 Dart Variables & Data Types
      • 2.2.3 Control Statements & Loops
      • 2.2.4 Functions & Classes
      • 2.2.5 Asynchronous Programming (Future & Stream)
    • 2.3 Flutter Widgets
      • 2.3.1 Stateless vs Stateful Widgets
      • 2.3.2 Material & Cupertino Widgets
      • 2.3.3 Layout Widgets (Row, Column, Stack)
      • 2.3.4 Container, Text, Image Widgets
      • 2.3.5 Responsive UI Design
    • 2.4 Navigation & Routing
      • 2.4.1 Navigator & Routes
      • 2.4.2 Named Routes
      • 2.4.3 Passing Data Between Screens
    • 2.5 State Management
      • 2.5.1 setState()
      • 2.5.2 Provider
      • 2.5.3 Riverpod / Bloc Overview
      • 2.5.4 State Management Best Practices
    • 2.6 API & Backend Integration
      • 2.6.1 REST API Concepts
      • 2.6.2 HTTP Package
      • 2.6.3 JSON Parsing
      • 2.6.4 Authentication & Authorization
    • 2.7 Device Features Integration
      • 2.7.1 Camera & Image Picker
      • 2.7.2 Location & Google Maps
      • 2.7.3 Push Notifications
      • 2.7.4 Local Storage
    • 2.8 Firebase with Flutter
      • 2.8.1 Firebase Setup
      • 2.8.2 Firebase Authentication
      • 2.8.3 Cloud Firestore
      • 2.8.4 Firebase Push Notifications
    • 2.9 App Testing & Deployment
      • 2.9.1 Debugging Flutter Apps
      • 2.9.2 Unit & Widget Testing
      • 2.9.3 Android App Build
      • 2.9.4 iOS App Build
      • 2.9.5 Play Store & App Store Deployment
    • 2.10 Projects & Case Studies
      • 2.10.1 Flutter UI Clone Project
      • 2.10.2 API-based Mobile App
      • 2.10.3 Firebase Integrated App
      • 2.10.4 Capstone Project

MERN Stack


DURATION

4 to 6 Months

PROJECT

1 Project

Prerequisite

Interest in Full Stack Web Development, No prior backend or framework experience required.

Contents

  1. MERN Stack Training Overview
    • 1.1 What are MERN Stack Course Pre-requisites
    • 1.2 Objectives of the MERN Stack Course
    • 1.3 Who should do the course
    • 1.4 MERN Stack Training Course Duration
  2. MERN Stack Course Content
    • 2.1 Web Development Fundamentals
      • 2.1.1 How the Web Works (Client–Server)
      • 2.1.2 HTTP/HTTPS & REST Concepts
      • 2.1.3 Frontend vs Backend
      • 2.1.4 Introduction to Full Stack Development
    • 2.2 HTML, CSS & JavaScript
      • 2.2.1 HTML5 Fundamentals
      • 2.2.2 CSS3, Flexbox & Responsive Design
      • 2.2.3 JavaScript Basics
      • 2.2.4 ES6+ Features
      • 2.2.5 DOM Manipulation
    • 2.3 React.js Frontend Development
      • 2.3.1 Introduction to React
      • 2.3.2 JSX & Components
      • 2.3.3 Props & State
      • 2.3.4 Hooks (useState, useEffect)
      • 2.3.5 React Router
      • 2.3.6 Forms & Validations
      • 2.3.7 API Integration with Axios
    • 2.4 Node.js & Express.js Backend
      • 2.4.1 Introduction to Node.js
      • 2.4.2 Express.js Framework
      • 2.4.3 MVC Architecture
      • 2.4.4 REST API Development
      • 2.4.5 Middleware & Error Handling
    • 2.5 MongoDB Database
      • 2.5.1 Introduction to MongoDB
      • 2.5.2 Collections & Documents
      • 2.5.3 CRUD Operations
      • 2.5.4 Mongoose ODM
      • 2.5.5 Schema Design & Relationships
    • 2.6 Authentication & Security
      • 2.6.1 User Registration & Login
      • 2.6.2 JWT Authentication
      • 2.6.3 Password Encryption (bcrypt)
      • 2.6.4 Role-based Access Control
    • 2.7 State Management & Advanced React
      • 2.7.1 Context API
      • 2.7.2 Redux Toolkit Basics
      • 2.7.3 Protected Routes
      • 2.7.4 Performance Optimization
    • 2.8 File Uploads & Real-time Features
      • 2.8.1 Image/File Upload
      • 2.8.2 Cloud Storage Basics
      • 2.8.3 Real-time Communication (Socket.io)
    • 2.9 Testing & Deployment
      • 2.9.1 API Testing with Postman
      • 2.9.2 Frontend Build Process
      • 2.9.3 Backend Deployment
      • 2.9.4 Environment Variables & Security
    • 2.10 Projects & Case Studies
      • 2.10.1 CRUD Web Application
      • 2.10.2 Authentication-based Project
      • 2.10.3 E-commerce / Blog Application
      • 2.10.4 Capstone MERN Project