Your question is Uncertainty in Gaussian Processes. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
Explain why uncertainty prediction is important in Gaussian Processes and how you estimate it.
Discuss the distinction between epistemic and observation noise uncertainty, derive the posterior predictive mean and variance, and explain how kernel choice and noise assumptions affect the result. Show how you would validate uncertainty quality using held-out data, including calibration, negative log-likelihood, and prediction interval coverage.