Explainable Artificial Intelligence (XAI) Concepts
DataCamp
Last updated June 30, 2026
An introduction to explainable artificial intelligence (XAI) — the practice of making AI systems' decisions understandable to the people affected by them. The course covers the core ideas of transparency, interpretability, and accountability, and the trade-off between how complex a model is and how easily it can be explained. It distinguishes model-specific explanations (tailored to one type of model) from model-agnostic ones (that work across models), and shows where each fits. The aim is to leave you able to judge when and how an AI system's reasoning should be opened up, so its decisions are not just effective but also justifiable. It is a conceptual course with no coding required. You can sample the opening chapter before subscribing; the full course and its Statement of Accomplishment are part of DataCamp Premium.
What you'll learn
- What explainable AI is and why transparency and trust matter
- Interpretability and accountability
- The trade-off between model complexity and explainability
- Model-specific vs model-agnostic explanation techniques
- Applying explainability across real-world use cases
- Making AI decisions justifiable
Frequently asked questions about Explainable Artificial Intelligence (XAI) Concepts
Is Explainable Artificial Intelligence (XAI) Concepts free?
No — Explainable Artificial Intelligence (XAI) Concepts is a paid course.
What are the prerequisites for Explainable Artificial Intelligence (XAI) Concepts?
None.
Does Explainable Artificial Intelligence (XAI) Concepts offer a certificate?
Yes. DataCamp Statement of Accomplishment on completion (requires DataCamp Premium).
Why we suggest this course
A beginner-friendly grounding for anyone who needs to trust, audit, or answer for AI decisions — analysts, product and risk staff, or newcomers curious about the "black box" problem. It is refreshingly honest about the real-world limits of explainability rather than treating it as a solved problem, and it gives you the vocabulary (interpretability, model-agnostic methods) to have the conversation with technical teams. One thing to know: the opening chapter is free to try, but the full course and its Statement of Accomplishment are part of DataCamp Premium.