Design of Experiments Courses and Certifications

Career Certificate

Modern Statistics for Data-Driven Decision-Making

6 ratings at Coursera

Learn probability, statistical inference and regression analysis, then apply Bayesian methods, classification and planned experiments using statistical computing in R to make data-driven decisions.

• Coursera
• 4 weeks, 10 hours a week
• Self-Paced
• Paid Course
• 4 courses

Classification and Planned Experiments

Build classification models with K-nearest neighbor and logistic regression in R and Python, then design, run, and analyze planned experiments including fractional factorial and computer experiments.

• Coursera
• 2 weeks, 3 hours a week
• Self-Paced
• Paid Course

Causal Inference Project Ideation

Design randomized field trials for causal inference: study company A/B testing, experiment ethics, difference-in-difference on observational data, and build an issue tree for referral bonus programs.

• Coursera
• 5 weeks, 2 hours a week
• Self-Paced
• Paid Course

Certified Lean Six Sigma Green Belt Training (Accredited)

2966 ratings at Udemy

Internationally accepted CSSGB, LSSGB Body of Knowledge + Summary Book + Certification - Get 26 PMI PDUs/PDCs/CPDs

• Udemy
• 1 day 1 hour 56 minutes
• Self-Paced
• Paid Course

ANOVA and Experimental Design

23 ratings at Coursera

Model differences between group means with one-way and two-way ANOVA and ANCOVA, then design experiments using randomization, blocking, replication, and factorial designs.

• Coursera
• 4 weeks, 10 hours a week
• Self-Paced
• Paid Course

Statistical Thinking for Industrial Problem Solving, presented by JMP

101 ratings at Coursera

Apply statistical thinking to industrial problems: explore data in JMP, build control charts, run hypothesis tests, fit linear and logistic regression, and design experiments.

• Coursera
• 10 weeks, 5 hours a week
• Self-Paced
• Free Online Course

Career Certificate

ASQ-Certified Six Sigma Black Belt (CSSBB) Exam Prep

68 ratings at Coursera

Prepare for the ASQ CSSBB exam: apply Six Sigma DMAIC tools, DFSS frameworks, design of experiments, and Lean methods while managing team roles and dynamics.

• Coursera
• 4 weeks, 10 hours a week
• Self-Paced
• Paid Course
• 3 courses

The DMAIC Framework: Analyze, Improve, and Control Phase

19 ratings at Coursera

Work through DMAIC's analyze, improve, and control phases: exploratory data analysis, correlation and regression, hypothesis testing, design of experiments, control charts, and control plans.

• Coursera
• 5 weeks, 2 hours a week
• Self-Paced
• Paid Course

Advanced Statistical Analysis and Tools

11 ratings at Coursera

Apply statistical tools across DMAIC phases: measurement system analysis, process capability, hypothesis testing, ANOVA, regression, design of experiments, and statistical process control for Black Belt work.

• Coursera
• 4 weeks, 2 hours a week
• Self-Paced
• Paid Course

MOST from a Methodological Perspective

Apply the multiphase optimization strategy (MOST) to intervention research: run factorial optimization trials, analyze them with factorial ANOVA, power the designs, and pinpoint effective intervention components.

• Coursera
• 7 weeks, 3 hours a week
• Self-Paced
• Paid Course

Manufacturing Process Control II

Learn how to control process variation, including methods to design experiments that capture process behavior and understand means to control variability.

• edX
• 8 weeks, 10-12 hours a week
• Self-Paced
• Free Online Course (Audit)

Coursera

Launch Effective A/B Tests

Design and launch online A/B tests with proper tracking, calculate performance uplift at 95% confidence, and weigh statistical against practical significance in rollout decisions.

• Coursera
• 2 weeks, 1 hour a week
• Self-Paced
• Paid Course

Coursera

Measure ML Impact & Business Value

Translate model metrics into money: build metric trees, design A/B and quasi-experiments, analyze lift with CUPED, and convert results into ROI, NPV, and executive dashboards.

• Coursera
• 3 weeks, 2 hours a week
• Self-Paced
• Paid Course

Coursera

Reproduce and Evaluate AI Research Workflows

Design reproducible machine-learning experiments: run controlled ablation studies, lock randomness, pin environments, version datasets, and track configurations to evaluate model changes and document results.

• Coursera
• 1 hour 46 minutes
• Self-Paced
• Paid Course

Data Analysis for Social Scientists

Learn probability, estimation, hypothesis testing, regression, instrumental variables, randomized experiments, and data visualization in R to answer social, economic, and policy questions.

• MIT OpenCourseWare
• Self-Paced
• Free Online Course