AI & ML – The AI Futurist (Ages 16-17)

AI & Machine Learning – The AI Futurist (Ages 16–17)

Empowering Young Minds to Build the Future—One Algorithm at a Time

What if your teen could go from asking “What is AI?” to training a robot to recognize faces, coding their own chatbot, or designing an app that solves real-world problems—all before turning 18?

At Tune‑Up Skills, we don’t just teach how technology works—we teach how to shape it.
Our AI & Machine Learning journey for ages 16–17 blends creativity, coding, and ethics into immersive, project‑based learning. Each lesson deepens both technical mastery and real‑world awareness—preparing students to become confident and responsible innovators.

Our mantra: 🎮 Play. 💡 Build. 🧠 Think. 🌐 Lead.

From visual games to sophisticated AI systems, students learn by building, testing, and presenting projects that use the same tools and methods as professional engineers and researchers. Every milestone and capstone project moves them one step closer to mastering the technologies shaping tomorrow.

Because the future isn’t just coming—it’s being coded by kids like yours.

Why This Program?

✅ Designed for ages 16–17 with progressive, year‑by‑year skill‑building
✅ Integrates creativity, coding, and ethical AI thinking
✅ Uses professional tools like Python, Scratch, and Teachable Machine
✅ Prepares students for careers in AI, robotics, and data science

Introduction & Guiding Philosophy

This curriculum follows a developmental pathway for learners aged 7–17, built on four teaching pillars:

• Spiral Learning – Revisiting key concepts at deeper levels each year

• Project‑Based Learning – Applying theory through creative and practical challenges

• Ethics at the Core – Promoting digital citizenship, fairness, and responsible use

• Progressive Tooling – Progressing from no‑code platforms to full Python and industry environments

Ages 16–17: The AI Futurist

Goal:
Master advanced AI concepts and complete a university‑ready or pre‑professional capstone project that showcases innovation, research, and technical skill.

Core Tools:
PyTorch, TensorFlow, Keras, OpenCV, GitHub, Google Colab Pro, AWS, Azure