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Carrie Grimes, Caroline Buckey, and Diane Tang

Take Udacity's Introduction to A/B Testing course and design and implement an A/B test to determine the efficacy of potential improvements to an online site or mobile app.

What's inside

Syllabus

Learn about what A/B testing is and what it can be used for.
Find out how to ensure experiment participants are adequately protected, and learn what questions you should be asking regarding the ethicality of experiments.
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Learn how to choose and validate metrics to use in your experiment.
Learn about how to design an A/B test.
Learn about how to analyze the results of your experiments.
Learn about the final project and go through a series of quizzes to verify the quantitative components of your test.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches concepts that are applicable to both websites and mobile apps
Covers design, implementation, and analysis of A/B tests
Emphasizes ethical considerations in A/B testing

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Reviews summary

Solid a/b testing course

This course explains the concept of A/B (split) testing quite well with lessons, quizzes, and a final project. It's good value for the time investment.
Quizzes at the right level of difficulty
Forums provide good support
Explains concepts well
Final project is both interesting and challenging

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in A/B Testing with these activities:
Review your notes from previous courses
Refresh your memory on related topics you've covered in previous courses to enhance your understanding of A/B Testing.
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  • Review your notes or textbooks
  • Take practice quizzes or tests
Refresh your basic statistics knowledge
Ensure you have a solid foundation in statistics to support your understanding of A/B Testing.
Browse courses on Statistics
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  • Review basic statistical concepts
  • Practice solving statistical problems
Participate in A/B Testing discussions
Engage with other students to discuss A/B Testing concepts and share your experiences.
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  • Join online forums or discussion groups
  • Participate in discussions and ask questions
  • Share your own insights and experiences
Five other activities
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Show all eight activities
Follow A/B Testing tutorials
Enhance your understanding of A/B Testing by following tutorials that provide step-by-step guidance.
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  • Follow tutorials on Udacity or other online platforms
  • Apply what you've learned to your own A/B Testing projects
Review 'Designing Data-Intensive Applications'
Review some of the fundamental concepts of data warehousing, such as denormalization, to strengthen your understanding of data intensive applications.
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Show steps
  • Read Chapters 1-3
  • Read the case study on Twitter's architecture
  • Solve the exercises at the end of the chapters
Solve A/B Testing problems
Reinforce your understanding of A/B Testing by solving problems that require you to apply the concepts you've learned.
Browse courses on A/B Testing
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  • Solve problems from the Udacity course or other online resources
  • Create your own A/B Testing problems and solve them
Create an A/B Testing project plan
Demonstrate your understanding of A/B Testing by creating a plan that outlines your hypothesis, metrics, and analysis strategy.
Browse courses on A/B Testing
Show steps
  • Define your research question and hypothesis
  • Identify your target audience
  • Choose your metrics
  • Design your experiment
  • Analyze your results
Write an A/B Testing blog post
Deepen your understanding of A/B Testing by explaining the concepts and sharing your insights in a blog post.
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  • Choose a topic related to A/B Testing
  • Research the topic and gather information
  • Write your blog post
  • Publish your blog post

Career center

Learners who complete A/B Testing will develop knowledge and skills that may be useful to these careers:
Web Developer
A Web Developer could directly implement the results of an A/B test to improve a site or app. By learning the concepts of A/B testing, a Web Developer can make more informed recommendations for improving metrics that are important to stakeholders.
Data Scientist
A Data Scientist can apply the insights gathered from an A/B test to make informed decisions to improve a site or app, potentially increasing profits or other key user metrics. Taking this course would provide aspiring Data Scientists with the necessary foundation to effectively design, implement, and analyze A/B tests under different real-world business constraints.
Product Manager
A Product Manager is often responsible for identifying and prioritizing potential improvements to a site or app. Having a strong understanding of A/B testing can help a Product Manager evaluate and prioritize these improvements, which can lead to a more successful product.
Data Analyst
A Data Analyst has the skills necessary to analyze the data from an A/B test and determine which changes are statistically significant. This course will provide a Data Analyst with the knowledge they need to interpret the results of an A/B test and communicate them to stakeholders.
User Experience Researcher
A User Experience Researcher can use the results of an A/B test to understand how users interact with a site or app. This information can be used to make improvements that enhance the user experience.
Marketing Manager
A Marketing Manager can use the results of an A/B test to improve the effectiveness of marketing campaigns. This course will help an aspiring Marketing Manager to apply principles of A/B testing to better target and optimize marketing efforts.
Business Analyst
A Business Analyst can use the results of an A/B test to analyze the potential impact of changes to a site or app. This information can be used to make informed decisions about which changes to implement.
Market Researcher
A Market Researcher can use the results of an A/B test to understand how users respond to different marketing messages. This information can be used to develop more effective marketing campaigns.
Digital Marketing Manager
A Digital Marketing Manager can use the results of an A/B test to improve the effectiveness of their digital marketing campaigns. By taking this course, a Digital Marketing Manager will learn the skills they need to design and implement A/B tests that can lead to improved performance.
Quantitative Analyst
A Quantitative Analyst can use their knowledge of mathematics and statistics to design and analyze A/B tests. This course will help a Quantitative Analyst learn the specific techniques that are used in A/B testing.
Growth Hacker
A Growth Hacker can use the results of an A/B test to identify opportunities to improve the growth of a site or app. By taking this course, a Growth Hacker will learn the skills they need to design and implement A/B tests that can lead to significant growth.
Software Engineer
A Software Engineer may be responsible for implementing the changes that are identified by an A/B test. By taking this course, a Software Engineer will gain the knowledge they need to understand the requirements of an A/B test and to implement the changes in a way that minimizes risk.
Product Designer
A Product Designer can use the results of an A/B test to evaluate the effectiveness of different designs. This information can be used to create more user-friendly and engaging products.
Consultant
A Consultant can use their knowledge of best practices in A/B testing to advise clients on how to improve their sites and apps. By taking this course, a Consultant will gain the skills they need to effectively design and implement A/B tests for their clients.
Statistician
A Statistician can use their knowledge of statistics to assist in the design and analysis of A/B tests. This course will help a Statistician learn the specific considerations and techniques that are used in A/B testing.

Reading list

We've selected 13 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in A/B Testing.
Introduces the fundamentals of bandit algorithms and their application to website optimization.
Introduces Bayesian statistics, which can be used to analyze A/B test results and make more informed decisions.
Provides a comprehensive overview of causal inference, which is essential for understanding the results of A/B tests and making valid conclusions.
Must-read for anyone who wants to learn about the lean startup methodology. It provides a practical framework for building and testing new products and services.
Provides a comprehensive overview of web analytics, which is essential for understanding the results of A/B tests and making data-driven decisions.
Provides a practical guide to designing and conducting experiments, including A/B tests, to maximize the information gained.
Provides a framework for developing good strategies, which can be used to inform the design of A/B tests.
Provides a comprehensive overview of data science, including data mining and data-analytic thinking, which are essential for designing and conducting effective A/B tests.
Provides a comprehensive overview of machine learning, including probabilistic models and algorithms, which can be used to analyze A/B test results.
Provides a comprehensive overview of statistical learning, including data mining, inference, and prediction, which are essential for designing and conducting effective A/B tests.

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