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Young Coders (Ages 12-16)

Build a strong foundation in computing with engaging, project-based learning. Students explore fundamental programming concepts, problem-solving approaches, and digital making through hands-on challenges across multiple tools and languages. This comprehensive course introduces artificial intelligence concepts, machine learning basics, and real-world AI projects that prepare students for the future of technology.

This pathway leads into our comprehensive GCSE and A-Level Computer Science preparation, where learners consolidate knowledge with intensive exam-style practice, past paper analysis, and deeper theory coverage. Students master advanced AI applications, machine learning algorithms, and real-world tech projects while developing critical thinking skills essential for university and future innovation careers.

3-Term Project-Based Curriculum

Term 1: Foundation & Programming Fundamentals

Building core computer science knowledge and Python programming skills

Module 1: Foundations of STEM & GCSE Computer Science

Topics:

• What STEM means in today's world
• GCSE Computer Science key areas (algorithms, programming, data, hardware, networking, cyber security, ethical issues)
• Problem-solving using computational thinking (decomposition, pattern recognition, abstraction, algorithms)

Learning Outcomes:

• Understand the STEM framework and its applications
• Explain key GCSE CS topics in simple terms
• Apply computational thinking to solve small problems

Creative Activities:

• Design a flowchart for a real-world process (e.g., making a sandwich, school timetable automation)
• Group quiz: Match STEM careers with technologies

Module 2: Python Programming (GCSE Focus)

Topics:

• Syntax & basics: variables, data types, input/output, operators
• Control structures: if-else, loops
• Data structures: lists, dictionaries, strings
• Functions & modular programming
• File handling basics
• GCSE-style programming challenges

Learning Outcomes:

• Write clean Python programs using GCSE exam-style questions
• Solve logic problems with loops and conditionals
• Use lists and dictionaries for structured data

Creative Activities:

• Build a text-based quiz game for GCSE revision
• Write a "Guess the Number" or "Rock, Paper, Scissors" game
• Mini data project: read and analyze a CSV file of student scores

Term 2: Web & App Development

Building interactive web experiences and mobile applications

Module 3: Web Development (Front-End Focus)

Topics:

• Introduction to the internet & how websites work
• HTML basics (structure, headings, paragraphs, images, links)
• CSS basics (colors, fonts, layouts, styling)
• JavaScript introduction (interactivity: buttons, events, DOM basics)
• Hosting a simple website (GitHub Pages or free hosting platforms)

Learning Outcomes:

• Design and structure a simple web page with HTML/CSS
• Add basic interactivity with JavaScript
• Publish a small personal webpage online

Creative Activities:

• Create a "GCSE Revision Website" with notes, quizzes, and tips
• Design a personal portfolio webpage
• Build a mini interactive webpage (e.g., digital flashcards)

Module 4: App Development

Topics:

• Understanding apps (native vs. web apps)
• Tools for beginners (MIT App Inventor, Thunkable, or Python Kivy)
• Designing user-friendly interfaces (UI/UX basics)
• Building a simple app (calculator, quiz app, or daily planner)

Learning Outcomes:

• Explain the difference between apps and websites
• Create a basic mobile app with a drag-and-drop or beginner-friendly framework
• Apply problem-solving to real-life needs

Creative Activities:

• Build a GCSE Formula Calculator app (Physics equations, Maths formulas)
• Make a "Habit Tracker" or "Daily Planner" app
• Group challenge: design an app that solves a school/community problem

Term 3: AI & Creative Projects

Exploring artificial intelligence and showcasing comprehensive STEM projects

Module 5: Introduction to Artificial Intelligence

Topics:

• What is AI? (History, Types: Narrow vs. General AI)
• AI in everyday life (recommendations, chatbots, self-driving cars)
• Machine Learning basics (training data, patterns, predictions)
• Hands-on intro: AI with Python libraries (e.g., simple chatbot with if-else or using a prebuilt ML tool like Teachable Machine)

Learning Outcomes:

• Explain AI concepts in GCSE-level language
• Understand ethical considerations of AI
• Build a simple rule-based AI program

Creative Activities:

• Create a chatbot that answers GCSE Computer Science revision questions
• Train an AI model (image classifier for objects, using Teachable Machine or similar tools)

Module 6: Creative Projects & Showcase

Topics:

• Combining Python, AI, Web, and Apps
• Teamwork & project management (agile sprints, roles: coder, designer, tester)
• Creativity in STEM (using coding for art, music, storytelling)

Learning Outcomes:

• Work collaboratively on a STEM project
• Present and explain technical solutions to non-technical audiences
• Build confidence in showcasing digital projects

Creative Activities:

• Hackathon-style project: "STEM for Good" – apps/websites that help solve real-world problems
• Create a digital art/music generator in Python
• Final showcase: students present projects (website, app, or AI tool)

Learning Outcomes

• Programming Mastery: Proficient in Python programming with GCSE-level competency
• Web Development Skills: Create interactive websites using HTML, CSS, and JavaScript
• AI Understanding: Grasp artificial intelligence concepts and build AI-powered projects
• App Development: Design and build mobile applications using modern tools
• Project Management: Plan, develop, and present comprehensive STEM projects
• Computational Thinking: Apply problem-solving approaches to real-world challenges
• Digital Citizenship: Understand ethical considerations in technology and AI
• Collaboration Skills: Work effectively in teams on complex projects

Assessment & Progression

• Project-Based Assessment: Each term culminates in major project showcases
• Progressive Complexity: Skills build systematically from basic to advanced concepts
• Portfolio Development: Students build a comprehensive portfolio of projects
• Peer Collaboration: Learn through team projects and peer presentations
• Real-World Application: Projects address real-world problems and challenges
• GCSE Preparation: Direct pathway to GCSE and A-Level Computer Science

Recommended ages: 11–18. Suitable for beginners and intermediates. This course provides a comprehensive foundation for GCSE and A-Level Computer Science preparation.