ThinkBeyondAI
LearnAI — courses by ThinkBeyondAI
Collaborators on the project
Shay Luo
Shay Luo
Ex-Kearney Partner & Founder. Combines consulting strategy with AI solutions.
Prof. Inhwa Kim
Prof. Inhwa Kim
Assistant Professor of Business at Oregon State University. AI scientist in human-AI interaction and AI in retail.

AI Basics

Understand how today's AI models really work, and where they fall short. Learn to use them with judgment instead of blind trust. Learn from industry experts and put it into practice in our AI City Quest mini-game. The essential starting point for anyone new to working professionally with AI.

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EXPLORE AI BASICS
EXPLORE AI BASICS
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AI Skills

Go from user to builder, step by step. Learn the practical skills that set you apart: coding with AI, using tools through MCPs, and designing workflows that automate real tasks. Build from your first prompt to complete AI systems in professional work environments.

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EXPLORE AI SKILLS
EXPLORE AI SKILLS
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Certificate · Built for EU AI Act literacy requirements

Building your first statistical model

How do you forecast a month that has not happened yet? An introduction to time series, built on a simple regression you can run yourself, and an honest look at where it fails.

Building your first statistical model

THINKBEYONDAI

The best professionals of the next decade won't ignore AI, and they won't trust it blindly either. They will be the ones who define what counts as correct in their field, not in spite of automation but through it.

ThinkBeyondAI exists to support exactly that: understanding how these systems work and recognizing where they fail, so that you remain the standard AI is measured against rather than the one it overtakes.

We study how AI is reshaping professional work and what it means for institutions whose authority rests on human judgment. And we go beyond theory: we show how the tools are used in everyday practice and create learning materials for teams and individuals.

Our work grows out of an international collaboration between students, professors and practitioners. Students bring the questions their future professions have stopped asking. Professors bring methodological rigor. Practitioners bring the reality of everyday work.

Think beyond the forecast.

Latest posts

(80 Posts)

Interview: An AI that answers the phone

Telefonagent's managing director on a system that answers missed calls for property managers, where the data sits, and what convinces callers.

by Nikolaus Fischer, Sep 17, 2026

Why AI does not answer neutrally

Raters preferred a 1.3-billion-parameter model over one with 175 billion. Alignment, RLHF, and why no answer comes out neutral.

by Tom Buchholz, Sep 16, 2026

Overparameterized, and still generalizing

Push a model past a perfect fit on its training data and test error starts falling again. Double descent, and what it did to learning theory.

by Tom Buchholz, Sep 16, 2026

Are small language models the future?

Phi-3 Mini runs on a laptop and beats models twice its size on Microsoft's own table. Why model size stopped being the first question.

by Emil Ohligs, Sep 16, 2026

Ten ways an LLM system gets attacked

The OWASP list for LLM applications, read from a finance desk: prompt injection, training-data leakage, and a supply chain of someone else's code.

by Emil Ohligs, Sep 16, 2026

How large language models work

A language model puts a probability on every possible next word, picks one, and runs the calculation again. Everything else follows from that loop.

by Emil Ohligs, Sep 16, 2026

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