Certified A/B Testing & Experimental Design

Certified A/B Testing & Experimental Design by Muhammad Shafiq is a comprehensive Udemy course that teaches you how to design, run, and analyze rigorous experiments for digital products. Updated July 2026, this free A/B testing course covers the statistical foundations, sample‑size calculations, and advanced multivariate techniques that professionals need to drive data‑driven growth. Learners gain practical templates, real‑world case studies, and a certification that validates expertise in experimental design. Whether you search for a “free A/B testing course,” an “A/B testing Udemy course,” or “learn A/B testing online,” this training delivers actionable skills for product managers, marketers, and CRO specialists.

What You'll Learn

• Build scientifically sound hypotheses that align with statistical testing frameworks.
• Master the calculation of sample size and optimal test duration using power analysis.
• Learn critical statistical concepts behind A/B testing, including p‑values, confidence intervals, and Type I/II errors.
• Understand how to design and implement complex experiments such as A/B/N tests and multivariate testing (MVT).
• Create robust primary, secondary, and guardrail success metrics (KPIs) for any experiment.
• Implement sequential testing and avoid common pitfalls like Sample Ratio Mismatch (SRM) and novelty effects.
• Apply ICE and PIE prioritization models to select high‑impact experiments.
• Analyze experimental results with confidence and present findings to stakeholders convincingly.

Course Details

• Instructor: Muhammad Shafiq
• Rating: 2.8 stars (based on student reviews)
• Language: English (en‑US)
• Certificate: Yes, upon completion
• Includes: Certification of completion, practical templates, real‑world case studies

What This Course Covers

Foundations of Experimental Design

• Definition of scientific hypotheses and their role in digital experimentation.
• Overview of the experimentation lifecycle from ideation to analysis.
• Key statistical terminology: p‑value, confidence interval, Type I/II errors.
• Common design flaws that lead to misleading results.

Statistical Power & Sample Size

• Principles of statistical power and how they affect experiment validity.
• Step‑by‑step calculation of required sample size for desired confidence levels.
• Determining optimal test duration to balance speed and reliability.
• Handling low‑traffic scenarios with sequential testing methods.

Advanced Test Structures

• Designing A/B/N tests that compare more than two variants.
• Implementing multivariate testing (MVT) to evaluate multiple factors simultaneously.
• Managing guardrails and secondary metrics to protect core business performance.
• Detecting and correcting Sample Ratio Mismatch (SRM) and novelty effects.

Metrics Selection & KPI Frameworks

• Choosing primary, secondary, and guardrail metrics aligned with business goals.
• Applying ICE (Impact, Confidence, Ease) and PIE (Potential, Importance, Ease) models for experiment prioritization.
• Building dashboards for real‑time monitoring of experiment health.
• Interpreting results to make data‑driven product decisions.

Practical Templates & Case Studies

• Ready‑to‑use experiment planning templates for product managers and marketers.
• Detailed case studies from leading tech companies demonstrating high‑impact experiments.
• Communication strategies for presenting statistical findings to non‑technical stakeholders.
• Scaling successful experiments across teams and platforms.

Who Should Take This Course

• Product Managers and Product Owners responsible for feature optimization.
• Digital Marketers, Growth Hackers, and CRO specialists seeking statistical rigor.
• Data‑savvy professionals who want to move from intuition to evidence‑based decisions.
• Beginners with a basic understanding of statistics who aim to become certified experiment designers.
• Mid‑level analysts looking to deepen their knowledge of multivariate testing and metric selection.

Prerequisites

• No prior experience needed — this course is beginner‑friendly.
• Basic familiarity with digital product terminology (e.g., conversion, KPI) is helpful but not required.
• Recommended: introductory knowledge of statistics or comfort with spreadsheet calculations.

Why Enroll in This Course

This training stands out because it blends statistical theory with hands‑on implementation, giving you the confidence to run defensible experiments. A free coupon provides 100 % off for a limited time, making the certification accessible without financial risk. Enrolling now (July 2026) ensures you benefit from the most up‑to‑date curriculum before the free offer expires. Compared with generic split‑testing tutorials, this program delivers a complete experimental design blueprint that employers value.

Course Highlights

• Lifetime access to all video lectures, templates, and case studies.
• Self‑paced learning allows you to progress on your own schedule.
• Certificate of completion validates your expertise in A/B testing and experimental design.
• Practical, industry‑tested frameworks such as ICE, PIE, and guardrail metrics.
• Real‑world case studies illustrate how leading companies achieve growth through experimentation.
• Mobile‑friendly content lets you study on any device, anytime.

Frequently Asked Questions

Q: Is this course really free?
A: Yes, the course can be accessed at no cost when you apply the current free coupon. The 100 % discount is available for a limited period, after which the standard Udemy price applies.

Q: What will I learn in this A/B testing course?
A: You will learn how to formulate data‑backed hypotheses, calculate sample size and test duration, master core statistical concepts, design complex A/B/N and multivariate experiments, select appropriate KPIs, and apply proven frameworks to drive measurable growth.

Q: Do I get a certificate after completing this course?
A: Absolutely. Upon finishing all modules and passing the final assessment, you receive a Udemy‑issued certificate that confirms your proficiency in experimental design and A/B testing.

Q: Is this course suitable for beginners?
A: Yes. The curriculum starts with foundational concepts and gradually introduces advanced techniques, making it ideal for beginners as well as professionals seeking deeper expertise.

Q: How long do I have to enroll for free?
A: The free coupon is available for a limited time, typically a few weeks from the date of publication. Enroll before the coupon expires to secure the 100 % discount and gain immediate access to all course materials.

Final Thoughts

Certified A/B Testing & Experimental Design equips product and marketing professionals with the statistical rigor and practical tools needed to run high‑impact experiments. If you aim to become a data‑driven decision‑maker and earn a recognized certification, this Udemy course is the right choice. Start your learning journey today and transform hypothesis into measurable growth.