Introducing AI with Scratch
Live: In-Person at ITU Lahore and Online
About Course
This summer camp is designed to introduce students to the world of programming through two popular languages: Scratch and Python. Over the course of two months, students will learn the fundamentals of programming concepts such as loops, variables, conditionals, and functions while transitioning from Scratch to Python. By the end of the camp, students will have the skills to create animations, games, and solve basic programming problems.
Week 1: Scratch Fundamentals
- Introduction to Scratch: Installation and interface overview
- Sprite Movement, Coordinate Axis, and Angles
- Advanced Scratch: Pen tool, Loops, and Variables
- Assignment: Scratch Letter Animation, Flowers pattern animations
Week 2: Introduction to Python
- Basics of Python: Print, Variables, and Data Types
- Python Loops and Input: while, for loops, Taking user input
- Assignment: Printing, Variables, Variable, Loops, Nested Loops
Week 3: Intermediate Python
- Advanced Loops and Conditions: Nested loops, Ifelse statements
- Building Applications with Functions: Age Calculator
- Assignment: IfElse Statements, Functions, Conditionals, Age Calculator
Week 4: Scratch Game Development
- Introduction to Scratch Games: Building a Maze Game
- Maze Runner II: Continuation of Maze Game development
- Assignment: Maze Game, Maze Runner II
Week 5: Advanced Python
- Advanced Python Concepts: Ifelse, ifelif statements, Lists
- Assignment: Lists
Week 6: Game Development in Scratch
- Space Invader Project: Ship Movement, Bullet, Cloning
- Collaborative Game Development: Let’s Help Each Other session
- Assignment: Space Invader Project
Week 7: Advanced Scratch Game Development
- Space Invader III: Continuation of Space Invader development
- Final Scratch Project Evaluation
Week 8: Python Data Structures
- Working with Strings and Arrays
- Assignment: Strings and Arrays
Week 9: Conclusion
- Wrapup and Final Session
- Assignment: Course Reflection and Feedback
- Certificate distribution and Celebration
This course provides a comprehensive journey from Scratch to Python, equipping students with essential programming skills and encouraging creativity through projectbased learning.
This summer camp is designed to introduce students to the world of programming through two popular languages: Scratch and Python. Over the course of four weeks, students will learn the fundamentals of programming concepts such as loops, variables, conditionals, and functions while transitioning from Scratch to Python. By the end of the camp, students will have the skills to create animations, games, and solve basic programming problems.
What Will You Learn?
- Understand Scratch’s interface and use it to create interactive projects.
- Integrate beginner-friendly AI tools within Scratch for hands-on learning.
- Build fun projects like chatbots, voice assistants, and image classifiers.
- Control sprite movement, animations, and respond to user interactions.
- Learn core machine learning concepts like decision-making and classification.
Practice debugging and refining code for smoother project performance.
Enhance creativity by customizing visuals, sounds, and logic flows.
Apply logical thinking and problem-solving strategies in every project.
Work collaboratively and share feedback during development.
Present a final AI-powered project with a personal, creative twist.
Certifications
“Introducing AI with Scratch”
June’2025-July’2025
Certified Students 🌟
Here you can view and download your certificates
With lifetime access to our lecture content,
Lecture 01: Emoji Reactions Using Machine Learning
Introduced AI and machine learning concepts in a kid-friendly way
Used Machine Learning for Kids to train a basic text classifier
Created two categories: Kind and Rude statements
Added multiple training examples for each category
Tested the model with new inputs to check accuracy
Connected the trained model to Scratch
Explored extra AI blocks in Scratch
Built an interactive project with an emoji sprite:
Happy face for kind input
Sad face for rude input
Discussed how AI makes it easier than traditional Scratch coding
Highlighted how ML handles complex variations in text
Objective: Show how AI brings smarter interactivity to Scratch projects
Lecture 02: Building a Smart Classroom
Trained a model to recognize classroom voice/text commands (e.g., “Fan On”, “Lamp Off”)
Added various training examples for each command
Focused on text recognition and classification
Tested the model with different sentences to check accuracy
Opened Scratch with AI blocks integrated
Used and modified the “Smart Classroom” Scratch template
Replaced standard logic with AI-based command recognition
AI model controlled fan/lamp sprites based on user input
e.g., “Turn on the light” → lamp switches on
“Switch off the fan” → fan turns off
Objective: Show how AI can interpret natural language and control actions
Key takeaway: AI reduces the need for manual coding by recognizing patterns in user input
Lecture 03:Creating an AI-Powered Pac-Man
Used Machine Learning for Kids to train a model that learns how to play Pac-Man based on player behavior
Focused on the “Recognizing Numbers” activity type
Steps:
Skipped manual training and jumped into Scratch via the “Make” section
Used a Pac-Man template and created variables for Pac-Man and Ghost positions (X and Y)
Added Machine Learning blocks to log positions during gameplay
Played the game 3–4 times to collect movement data
Saved the project, then trained the model using the collected data
Reopened Scratch and updated the code with AI decision-making blocks
Now, the AI-controlled Pac-Man avoided the ghost based on learned behavior
Lecture 04: Teaching AI to Sort Images
- Introduced image recognition using a “Recognizing Images” project.
- Objective: Train a model to classify images as either Car or Cup.
- Students uploaded real images under each label instead of text.
- Trained the model via the “Learn and Test” option.
- Used the “Cars and Cups” Scratch template in the Make section.
- Integrated ML blocks in Scratch to let the AI analyze and sort images automatically.
- Outcome: Students created an interactive project where AI identified and sorted images without manual feature coding.
- Key Learnings: Hands-on AI image classification, using visual data for training, and understanding how AI mimics human-like recognition.
Lecture 05: Recognizing Sounds
Introduced sound recognition using a “Recognizing Sounds” project.
Train a model to recognize voice commands (“right” and “left”).
Students recorded background noise under the built-in label to help the model ignore irrelevant sounds.
Created custom labels: Right and Left, and recorded voice samples for each.
Trained the model using the “Learn and Test” option.
Used the “Alien Language” Scratch template in the Make section.
Integrated ML blocks in Scratch to connect the trained model with sprite action.
Lecture 06: Postal Sorting Office
Introduced AI-based handwriting recognition using Machine Learning for Kids.
Project type: Recognizing Text – focused on reading handwritten postal codes.
Created 3 labels representing different cities or categories in the Train section.
Used the Draw tool to input handwritten initials under each label.
Trained the model to recognize these handwritten examples.
Tested the model’s accuracy by drawing new samples for classification.
Opened Scratch 3 and used the Mailman Max template in the Make section.
Customized the “Postal Code” sprite with students’ handwritten versions.
Integrated the trained model using ML blocks to classify and sort mail automatically.
Learned how AI can classify handwriting, build datasets, and apply ML to real-world tasks.
Lecture 07: Travel Chatbot
Students built a travel chatbot using Machine Learning for Kids with a focus on text recognition.
The AI model was trained to understand tourist preferences from natural language input.
Multiple labels were created (e.g., Gallery, Park, Bank), each representing a type of place.
Text examples were added under each label to teach the AI relevant phrases and intents.
Example: “I love paintings” → Gallery, “I need cash” → Bank.
The model was trained and tested to recognize and classify new input sentences.
Students used the “Tourist Info” Scratch template to build the chatbot.
Machine learning blocks were integrated into Scratch to connect user input to place suggestions.
The chatbot could analyze typed sentences and suggest suitable places using the trained AI.
Students learned about intent recognition, AI integration with Scratch, and building smart assistants.
Lecture 08: Rock, Paper, Scissors
Students created a Rock, Paper, Scissors game using Machine Learning for Kids.
The project focused on image recognition through webcam input.
Three labels were created: Rock, Paper, and Scissors.
Students captured at least 15 images per gesture using the webcam.
Examples: fist for rock, flat palm for paper, two fingers for scissors.
Trained the model to recognize these gestures accurately.
Tested the model by showing new hand gestures in front of the webcam.
Used Scratch to develop the game using a pre-built template.
Connected the trained model to Scratch using machine learning blocks.
The webcam detected the player’s move in real-time.
The computer randomly selected its own move.
The program compared both moves and showed win, lose, or draw.
Students played using real hand gestures, making the game interactive.
Learned how AI can recognize live images and enhance simple games.