Professional Mastery Tracks

This is the essential first step into machine learning. Students build confidence by tackling a real-world classification problem and delivering a complete predictive model from start to finish.

This workshop provides modern AI literacy, focusing on advanced prompt engineering and the critical ethical implications of generative models. This is essential for IB TOK and CAS.

An exciting, hands-on introduction to neural networks and image data. This workshop makes the complex topic of deep learning accessible and fun, culminating in a functional image recognition model.

This workshop covers the entire pipeline for transforming raw text into machine-readable data for real-world applications like content moderation. A key skill for aspiring CS students.

This premier offering moves beyond using models to mastering their architecture, culminating in a production-ready Retrieval-Augmented Generation (RAG) system. A true portfolio differentiator.

Unleash student creativity. This workshop teaches participants to orchestrate powerful AI models to generate stunning visuals, video, and audio without writing a single line of code.

Move beyond basic models to tackle complex regression and time-series forecasting. This course is for students who want to master techniques that win Kaggle competitions.

A code-first workshop on building real applications with generative models. Go beyond prompting and learn to integrate LLMs into software using APIs and modern tools like Genkit.

Gain a decisive edge in competitions like FIRST and VEX. This workshop focuses on applying Computer Vision to solve common robotics challenges like object detection and navigation.

A high-level course for future leaders. Move beyond discussion to quantitatively audit AI models for bias and fairness, creating a portfolio piece that demonstrates exceptional maturity.

The pinnacle of AI and engineering. Use generative design to invent and optimize a custom robotic component, then bring it to life with 3D printing. A one-of-a-kind portfolio piece.

A strategic guide for educators on navigating the complexities of AI integration, focusing on academic integrity, compliance with the DPDP Act, and creating a "zero-burden" implementation plan.