BOCPD study guide
BOCPD · Work through your exam, one topic at a time.
The BOCPD credential is designed for professionals who want to demonstrate competence in the domains outlined in its exam content outline. Because the exam name is an acronym, candidates should confirm the exact scope with the certifying organization. The exam is structured around four equally weighted domains, each covering a distinct area of practice. Typical candidates include practitioners seeking formal recognition, career changers building credibility, and team leads who need a shared vocabulary for process improvement. The BOCPD study guide has 4 sections and about 1,590 words.
01Domain 1: Foundations of Bayesian Online Changepoint Detection
Bayesian online changepoint detection (BOCPD) treats a data stream as a sequence of segments, each generated by a fixed model, with abrupt switches at changepoints. The central quantity is the run length r t : the number of observations since the most recent changepoint.
426 words, about 2 min02Domain 2: Segment Models, Priors, and Predictive Distributions
BOCPD is only as good as the predictive distribution it uses within a segment. The standard construction pairs a conjugate prior with a likelihood so that the posterior over segment parameters has a closed form and the predictive p(x t segment data) can be computed exactly.
424 words, about 2 min03Domain 3: The Recursive Algorithm, Pruning, and Computational Control
At time t , maintain a vector of unnormalized run-length weights w t(r) for r = 0, , t . For each previous run length r' , compute the predictive ^{(r')} = p(x t r', data) and the hazard H(r') .
390 words, about 2 min04Domain 4: Interpretation, Calibration, and Evaluation
The primary output is the run-length posterior over time, often visualized as a heat map. A sharp concentration of mass near short run lengths signals a changepoint; a diagonal ridge moving rightward indicates a stable segment.
350 words, about 2 min