Frequently Asked Questions

Basic statistics helps, but you don’t need advanced math. We include short primers on practical concepts used in marketing ML: AUC/ROC, cross-validation, calibration, and uplift evaluation. If you can interpret charts and reason about experiments, you’ll be fine.

Yes. After you complete the final assessment, you receive a verifiable digital certificate you can share on LinkedIn and include in your CV. It includes a completion date and a unique validation ID.

We offer self-paced modules, cohort-based learning with weekly live sessions, and intensive bootcamps. Depending on your plan, you may also get mentor office hours, assignments, and project reviews.

Support includes Q&A forums, structured office hours, and feedback on project submissions (plan-dependent). You can also ask questions through the form on this page; we typically respond within 1–2 business days.

You should be comfortable with basic marketing metrics and spreadsheets. Familiarity with Python is helpful but not mandatory for every track. We provide guided notebooks and step-by-step walkthroughs for core exercises.

Most learners progress with 4–6 hours/week. Cohorts typically include one live session plus assignments. Bootcamps are more intensive and can require 10–15 hours/week during peak project weeks.

Refund eligibility depends on the course format and start date. For cohorts, refunds are usually available before the first live session. For self-paced access, refunds may be available within a limited window if course progress is minimal.

Yes: conversion prediction, churn, LTV estimation, creative testing, personalization, uplift modeling, and measurement strategy. We emphasize decision-making and validation so models translate into business impact.