Workshops Offered

? Introduction to Smart Robotics: Basics of robotics, automation, and intelligent systems
? Robot Hardware Components: Sensors, actuators, microcontrollers, and power systems
? Programming Foundations: Coding robots using Python or Arduino (C++)
? Motor & Sensor Control: Hands-on with motors, IR, ultrasonic, and light sensors
? Building Smart Robots: Create line-followers, obstacle avoiders, and reactive bots
? Wireless & IoT Integration: Control robots via Bluetooth, Wi-Fi, or web apps
? Automation Logic & Decision Making: Implement feedback loops and smart behavior
? Introduction to AI in Robotics: Optional add-on using computer vision and ML basics
? Robot Simulation Tools: Use virtual platforms like TinkerCAD or Webots
? Autonomous Systems: Explore navigation, mapping, and real-time adjustments
? Mini Projects: Build simple automation systems and smart gadgets
? Team Collaboration: Work in groups to solve real-world robotic challenges
? Capstone Project: Design, code, and demo your own smart robot
? Showcase & Presentation: Present projects to peers and mentors
? Certificates & Recognition: Earn a certificate of completion and prizes for top teams

? Introduction to Data Science: What is data science and why it matters in today’s world
? Data Collection & Cleaning: Learn how to gather, clean, and prepare real-world data
? Exploratory Data Analysis (EDA): Use graphs, charts, and stats to uncover hidden patterns
? Spreadsheets to Python: Transition from Excel to Python using pandas and Jupyter notebooks
? Data Visualization: Create eye-catching visual stories with matplotlib, seaborn, and plotly
? Statistics Made Fun: Understand mean, median, mode, correlation, and probability
? Intro to Machine Learning: Use beginner-friendly models like decision trees and k-NN
? Solve Real-Life Mysteries: Analyze datasets from sports, music, environment, and more
? Mini Projects: Hands-on projects like predicting grades or analyzing social media trends
? Ethics in Data Science: Discuss bias, privacy, and responsible data use
? Storytelling with Data: Turn insights into presentations and data dashboards
? Collaborative Challenges: Team up to crack data puzzles and win mini-hackathons
? Capstone Project: Investigate a real-world question and present your findings
? Demo Day & Certificates: Showcase your work to mentors, parents, and peers
? No Prior Coding Needed: Learn everything from the ground up — just bring curiosity!

? Intro to Android Development: Understand mobile apps, Android ecosystem & tools
? Setting Up the Environment: Install Android Studio and explore the IDE
? Java for Android: Learn core Java concepts: variables, conditionals, loops, OOP
? UI Design with XML: Design clean and interactive layouts using XML in Android Studio
? Activity Lifecycle: Understand how Android apps run and manage screen changes
? User Input & Navigation: Add buttons, text fields, and multi-screen navigation
? Data Storage: Use SharedPreferences and SQLite for saving user data
? Working with APIs: Fetch and display data from the internet using JSON and REST APIs
? Media & Sensors: Add audio, video, and use device sensors like GPS & accelerometer
? Debugging & Testing: Learn to troubleshoot, test, and polish your apps
? Mini Projects: Build simple apps like to-do lists, quiz apps, or calculators
? Play Store 101: Learn the basics of publishing an app on the Google Play Store
? Capstone App Project: Design and develop your own unique Android app
? App Showcase: Present your app to mentors, peers, and receive feedback
? Beginner-Friendly: No prior experience needed — just passion and creativity!

? Introduction to AI & Machine Learning: What is AI, ML, and how it’s changing the world
? Python Basics for AI: Learn Python fundamentals—variables, loops, functions, and logic
? Working with Data: Load, clean, and analyze datasets using pandas and NumPy
? Data Visualization: Use matplotlib and seaborn to tell stories with data
? Core Machine Learning Concepts: Learn supervised vs unsupervised learning
? Popular ML Algorithms: Explore decision trees, k-NN, and linear regression
? Model Building in Scikit-learn: Train, test, and evaluate your first ML models
? Hands-on with Real Datasets: Work on beginner-friendly datasets (Titanic, Iris, etc.)
? Intro to Neural Networks: Get a peek into deep learning with simple neural nets
? Ethics in AI: Understand fairness, bias, and responsible AI development
? Mini Projects: Predict outcomes, classify images, or detect fake news
? Capstone Project: Build and present your own end-to-end AI-powered solution
? Collaboration & Code Sharing: Work in teams using Jupyter Notebooks and GitHub
? AI Showcase & Feedback: Present projects and receive mentorship feedback
? No Experience Needed: Designed for beginners with step-by-step guidance