Individual Courses Offered

1. Introduction to MS Office
2. MS Word Basics – Formatting & Document Creation
3. Advanced MS Word – Tables, Mail Merge & Collaboration
4. MS Excel Basics – Data Entry & Formatting
5. Excel Formulas & Functions for School Projects
6. Data Visualization with Charts & Graphs in Excel
7. PowerPoint Basics – Creating Engaging Presentations
8. Advanced PowerPoint – Animations & Multimedia
9. OneNote – Digital Note-Taking & Organization
10. AI & Smart Features in MS Office
11. Real-World Applications – School Reports & Projects
12. Final Project & Productivity Tips for Students

1. Introduction to Scratch
2. Understanding Scratch Blocks
3. Events and Sequences
4. Loops and Repetition
5. Using Conditions (If-Else Statements)
6. Variables and Operators
7. Creating Interactive Stories
8. Functions (Custom Blocks)
9. Using Lists and Data Handling
10. Advanced Animations
11. Creating Games – Basics
12. Enhancing Games – Advanced Features
13. Project Work – Mini Challenge
14. Final Project and Showcase

1. Introduction to MIT App Inventor
2. Understanding the App Inventor Interface
3. Designing User Interfaces (UI)
4. Working with Components and Properties
5. Using Blocks for Logical Programming
6. Handling User Input and Events
7. Variables and Data Storage
8. Implementing Conditional Statements and Loops
9. Working with Media (Images, Sounds, and Videos)
10. Using Sensors (Accelerometer, GPS, etc.)
11. Connecting to Databases (TinyDB and Firebase)
12. Integrating Web APIs and Online Services
13. Developing and Testing a Complete Mobile App
14. Publishing and Sharing Apps

• Python fundamentals
• Introduction to Python
• String handling
• Control flow tools
• Function
• Python data structures
• Module and packages
• List, Set, Dictionary, Comprehension
• Introduction to OOP
• Encapsulation
• Using objects
• Inheritance
• Abstract classes
• Exception handling
• Search algorithms
• Sort algorithms
• Case studies, Project work

• Getting Started - What is the web?
• HTML - structuring websites
• CSS - styling websites
• HTML 5
• JavaScript
• jQuery
• Bootstrap
• Project

• Graphic design is the craft of planning and creating visual content to communicate ideas and messages. Design can be used to promote and sell products, convey a message, or develop a brand identity. Though some graphic design has a commercial purpose, graphic design can also be a form of art and expression.

• Introduction to ethical hacking
• Footprinting and reconnaissance
• Scanning network
• Enumeration
• System hacking
• Trojans and backdoors
• Hacking webservers
• Hacking web applications
• Cryptography
• Penetration testing

This beginner-friendly course introduces young learners (Grades 3–5) to the exciting world of robotics and coding through interactive, hands-on activities. Students will explore the fundamentals of robotics, learn to program simple robots using block-based coding, and develop problem-solving skills through fun, creative challenges.

Through guided lessons and engaging projects, students will:
✅ Understand basic robotics concepts and how robots work.
✅ Learn block-based programming (such as Scratch or similar platforms).
✅ Build and control simple robots using sensors and motors.
✅ Develop logical thinking and problem-solving skills.
✅ Participate in exciting team-based challenges and projects.

This course fosters creativity, teamwork, and computational thinking, providing a strong foundation for future STEM learning. No prior coding or robotics experience is required—just curiosity and a willingness to explore!

✅ Basics of Robotics: Understanding components like motors, sensors, and controllers
✅ Introduction to Coding: Writing simple programs using block-based and text-based programming
✅ Hands-on Assembly: Building and testing basic robotic models
✅ Sensor Integration: Working with IR, ultrasonic, and other sensors for automation
✅ Real-World Applications: Designing and coding robots to perform specific tasks

✅ Advanced Robotics Concepts: Working with motors, actuators, and microcontrollers
✅ Programming & Automation: Writing efficient code for robotic control
✅ Sensor Fusion: Using multiple sensors (IR, ultrasonic, gyroscope) for navigation
✅ Wireless Communication: Controlling robots via Bluetooth/WiFi modules
✅ AI & Robotics: Basics of machine learning and computer vision for smart robots
✅ Project-Based Learning: Designing and building an autonomous robot

✅ Introduction to AI: Understanding AI, machine learning, and deep learning
✅ Python for AI: Basics of Python programming and libraries like NumPy & Pandas
✅ Supervised vs. Unsupervised Learning: Understanding different learning techniques
✅ Neural Networks & Algorithms: Basics of how AI models learn and make decisions
✅ Hands-On Projects: Building simple AI models for text, images, and predictions
✅ Ethics & AI: Understanding responsible AI and its impact on society

✅ Basics of Robotics: Understanding components like motors, sensors, and controllers
✅ Introduction to Coding: Writing simple programs using block-based and text-based programming
✅ Hands-on Assembly: Building and testing basic robotic models
✅ Sensor Integration: Working with IR, ultrasonic, and other sensors for automation
✅ Real-World Applications: Designing and coding robots to perform specific tasks

✅ Advanced Robotics Concepts: Working with motors, actuators, and microcontrollers
✅ Programming & Automation: Writing efficient code for robotic control
✅ Sensor Fusion: Using multiple sensors (IR, ultrasonic, gyroscope) for navigation
✅ Wireless Communication: Controlling robots via Bluetooth/WiFi modules
✅ AI & Robotics: Basics of machine learning and computer vision for smart robots
✅ Project-Based Learning: Designing and building an autonomous robot

✅ Advanced Robotics & Automation: Designing and programming autonomous robots
✅ IoT & Cloud Integration: Connecting robots to the cloud for remote monitoring and control
✅ Wireless Communication: Using Wi-Fi, Bluetooth, and MQTT for real-time data exchange
✅ AI & Machine Learning in Robotics: Implementing basic AI models for smart decision-making
✅ Embedded Systems & Microcontrollers: Working with ESP8266, Raspberry Pi, or Arduino
✅ Hands-on Projects: Building IoT-enabled robots for smart applications

✅ Introduction to App Development: Understanding mobile platforms and frameworks
✅ User Interface (UI) Design: Creating visually appealing and user-friendly apps
✅ Fundamentals of Programming: Learning basic coding concepts (JavaScript, Dart, or Swift)
✅ Building Functional Apps: Developing simple, interactive applications
✅ Debugging & Testing: Ensuring app performance and usability
✅ Deployment Basics: Running apps on simulators and real devices

✅ Introduction to AI: Understanding AI, machine learning, and deep learning
✅ Python for AI: Basics of Python programming and libraries like NumPy & Pandas
✅ Supervised vs. Unsupervised Learning: Understanding different learning techniques
✅ Neural Networks & Algorithms: Basics of how AI models learn and make decisions
✅ Hands-On Projects: Building simple AI models for text, images, and predictions
✅ Ethics & AI: Understanding responsible AI and its impact on society

✅ Data Science Fundamentals: Data collection, preprocessing, and feature engineering
✅ Machine Learning Techniques: Supervised and unsupervised learning models
✅ Deep Learning Basics: Understanding neural networks and AI model training
✅ Data Visualization: Exploring trends and patterns using Matplotlib and Seaborn
✅ Python for AI & Data Science: Using NumPy, Pandas, Scikit-Learn, and TensorFlow
✅ Real-World AI Applications: Building projects in image recognition, sentiment analysis, and

✅ Introduction to AI & Data Science: Understanding core concepts, applications, and future trends
✅ Python for AI & Data Science: Working with NumPy, Pandas, and Matplotlib for data handling and visualization
✅ Data Preprocessing & Feature Engineering: Cleaning and preparing data for AI models
✅ Machine Learning Fundamentals: Supervised and unsupervised learning using Scikit-Learn
✅ Deep Learning Basics: Introduction to neural networks and TensorFlow/Keras
✅ Data Visualization & Analytics: Identifying insights using Matplotlib, Seaborn, and Power BI/Tableau
✅ Real-World Applications: Working on AI-driven projects such as sentiment analysis, fraud detection, and image recognition

✅ Advanced Machine Learning: Reinforcement learning, ensemble methods, and optimization techniques
✅ Deep Learning & Neural Networks: Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Transformers
✅ Natural Language Processing (NLP): Sentiment analysis, chatbots, and language modeling
✅ Computer Vision: Image classification, object detection, and face recognition
✅ AI Model Deployment: Deploying AI models using Flask, FastAPI, or TensorFlow Serving
✅ Ethics & Bias in AI: Understanding fairness, explainability, and responsible AI development
✅ Hands-on Projects: Developing AI applications in healthcare, finance, and automation