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Explore Data Science Essentials – Crash Course in A/B Testing with Case Study with 104,732 views, 2,411 likes, and 46 comments. Experience the impact of this video content that has captured audience attention.

In this applied Data Science Crash Course, we cover everything you need to know about A/B testing, from the concepts to the practical details they can apply in business. The course merges in-depth statistical analysis (think hypothesis testing, significance levels, and the nitty-gritty of pooled estimates, test statistics, p-values, and assessing statistical significance) with the kind of data science theories big tech firms rely on, all alongside practical Python tutorials for real-world test implementation. Plus, there's a real-life case study thrown in to help you understand the concepts more. ✏️ Course created by Tatev Karen Aslanyan. More from Tatev here: https://lunartech.ai/ ⭐️ Contents ⭐️ ⌨️ (0:00:00) Video Introduction ⌨️ (0:03:49) Introduction to Data Science and A/B Testing ⌨️ (0:05:38) Basics of A/B Testing in Data Science ⌨️ (0:07:06) Key Parameters of A/B Testing for Data Scientists ⌨️ (0:09:24) Formulating Hypotheses and Identifying Primary Metrics in Data Science A/B Testing ⌨️ (0:19:55) Designing an A/B Test: Data Science Approach ⌨️ (0:37:56) Resources for A/B Testing in Data Science ⌨️ (0:39:22) Analyzing A/B Test Results in Python: Data Science Techniques ⌨️ (1:01:00) Data Science Portfolio Project: Case Study with AB Testing ⌨️ (1:04:38) Reintroduction to A/B Testing in the Data Science Process ⌨️ (1:21:07) Data Science Techniques: Loading Data with Pandas for A/B Testing ⌨️ (1:29:19) Data Science Visualization: Using Matplotlib and Seaborn for A/B Test Click Data ⌨️ (1:38:38) Data Science Power Analysis: Understanding A/B Test Model Parameters ⌨️ (1:44:25) Data Science Calculations: Pooled Estimates and Variance for A/B Testing ⌨️ (2:06:48) Computing A/B Test P-Values: Data Science Methods for Statistical Significance ⌨️ (2:12:42) Practical Significance in A/B Testing: A Data Science Perspective ⌨️ (2:29:07) Conclusion: Wrapping Up A/B Testing in Data Science 🎉 Thanks to our Champion and Sponsor supporters: 👾 davthecoder 👾 jedi-or-sith 👾 南宮千影 👾 Agustín Kussrow 👾 Nattira Maneerat 👾 Heather Wcislo 👾 Serhiy Kalinets 👾 Justin Hual 👾 Otis Morgan 👾 Oscar Rahnama -- Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://freecodecamp.org/news ❤️ Support for this channel comes from our friends at Scrimba – the coding platform that's reinvented interactive learning: https://scrimba.com/freecodecamp

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