Develop essential data science & ai skills with expert instruction and practical examples.
Whether you've got a lean startup or a fat Fortune 500, the faster you learn the faster you'll grow. Optimization and a/b testing is at the heart of learning fast. I guarantee you will learn something in this course that will raise your skill level.
With the 30-day money-back guarantee, you can't lose. We start with the basics, then cover the 8 steps of running a solid a/b test. Next we dive deep into the statistics behind hypothesis testing.
In the long-run you will save your organization headaches by setting up tests correctly and analyzing them with the right statistical rigour. There is double and triple digit ROI around optimization for companies that figure it out. Start now and impress your colleagues on Monday morning.
Topics include: Examples of a/b tests Hypothesis testing Measurement as risk reduction Selecting a KPI or success metric 8 Steps for Running an A/B Test Selecting from amongs a/b test and MVT test designs Lift Threshold Null Hypothesis Statistical significance Sample size estimates confidence interval test statistic t-tests standard error of the mean chi-square Fischer Exact test Statistical Power Type I error Type II error p-values How to choose what statistical test to run.
View pricing and check out the reviews. See what other learners had to say about the course.
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