Marketing Campaign A/B Testing 102
Unleash data-driven decision-making in your marketing campaigns. Our hands-on course empowers you to optimize strategies with Python-conducted A/B tests on means and proportions.
Complete the course to receive a take-home challenge. Analyze a provided dataset, design an A/B test, and present actionable recommendations. Gain personalized feedback and showcase your skills for success in data-driven marketing.
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Lession 1: Power Analysis Intro
Discuss the concept of power analysis and elucidate its significance in A/B Testing.
Discuss the concept of power analysis and elucidate its significance in A/B Testing.
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Lesson 2: Power Analysis Python Walkthrough
Illustrate the procedure of utilizing Google Colab and Python scripts to conduct power analysis.
Illustrate the procedure of utilizing Google Colab and Python scripts to conduct power analysis.
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Lesson 3: Set up A/B Test
Describe the process of configuring and executing A/B tests. Outline the steps in the test setup, which may involve internal tools or collaboration with software engineers for assistance. Lastly, address the aspects of data collection and enlist the support of data engineers for A/B test analysis.
Describe the process of configuring and executing A/B tests. Outline the steps in the test setup, which may involve internal tools or collaboration with software engineers for assistance. Lastly, address the aspects of data collection and enlist the support of data engineers for A/B test analysis.
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Lesson 4: Validity Checks Intro
Explore the methodology for performing validity checks, encompassing the AA test, SRM, and Novelty Effect.
Explore the methodology for performing validity checks, encompassing the AA test, SRM, and Novelty Effect.
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Lesson 5: Validity Checks Python Walkthrough
Using Python to perform the AA test, SRM, and examine the Novelty Effect.
Using Python to perform the AA test, SRM, and examine the Novelty Effect.
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Lesson 6: Statistical Inference Intro
Elaborate on the process of conducting statistical inference for an A/B test.
Elaborate on the process of conducting statistical inference for an A/B test.
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Lesson 7: Statistical Inference Python Walkthrough
Walk through the procedure for performing statistical inference with Python.
Walk through the procedure for performing statistical inference with Python.
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Lesson 1: A/B Testing Proportion Case Intro
Introduce a case involving proportion A/B testing and demonstrate how to utilize Python to carry out this test.
Introduce a case involving proportion A/B testing and demonstrate how to utilize Python to carry out this test.
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Lesson 2: A/B Testing Proportion Case Python Walkthrough
Illustrate the application of Python for conducting the test and explain how it distinguishes itself from mean-based tests.
Illustrate the application of Python for conducting the test and explain how it distinguishes itself from mean-based tests.
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Congratulations!
Congratulations to all participants for successfully finishing the course, and express gratitude for placing your trust in Datanough. If you're keen to explore further topics like A/B Testing 101 and A/B Testing Interviews, feel free to visit our Datanough Academy website.
Congratulations to all participants for successfully finishing the course, and express gratitude for placing your trust in Datanough. If you're keen to explore further topics like A/B Testing 101 and A/B Testing Interviews, feel free to visit our Datanough Academy website.
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