Product Experimentation: AB Testing in R with Interview Prep

Data Science, AB Testing, Multivariate Test, Multi-armed Bandit, Statistics, R Coding, A/B Testing Interview questions

What you'll learn

How companies like Google, Facebook, Amazon use Product Experimentation to launch successful products
Excel in Product Experimentation & A/B Testing interviews
A/B Testing, Multivariate Testing & Multi-armed Bandit Testing
Hypothesis testing, including inferential statistics, significance level, type I and II errors, test statistics, p-values, statistical significance and statistical power
End to end process from hypothesis generation & design to implementation & analysis
Real world examples from Amazon, AirBnb, Square, Uber
Relevance of statistics and how each statistical concept fits in the big picture of A/B testing
Sample size calculation and test results analysis using R
Use experimentation to optimize websites and app
Sample size calculation using online calculators
Use experimentation to increase conversion on landing pages or in-app campaigns
Templates & Cheatsheet to generate, prioritize and analyze A/B tests


Requirements

You should have basic knowledge of statistical concepts such as mean, standard deviation and variance

Description

Have you always wondered how companies like Google, Facebook, Amazon use experimentation to launch successful products?

Do you want to apply product experimentation at your start-up or your current role?

Or maybe you are interviewing for a role in big Tech and wondering how to succeed in those interviews?


With the rise of smartphones, Product testing has really come to the forefront. If you do a google search for Experimentation or A/B testing, you will come across thousands of blogs and articles that discuss this topic. Unfortunately, most of them are either full of inaccuracies and misinterpretation of mathematical concepts Or they are too difficult to understand. This is not surprising. A/B testing is a deep area - there are many nuances involved throughout the process from conceptualization & design all the way to implementation & analysis. This course addresses this. I have designed this course to go deep into important statistical concepts but in a way that is easy to understand using everyday examples.


In just two hours, you will learn -

What product experimentation is and how to do it right

What is A/B Testing, Multivariate Testing and Multi-armed Bandit Testing

What is the relevance of statistics in AB testing

What do statistical concepts such as confidence intervals, Type 1, Type 2 errors, p-value, statistical significance and statistical power mean And how do they fit in the big picture

And How to calculate sample size and duration for a successful A/B test


All these concepts will be reinforced with real world examples from companies such as Amazon, AirBnb, Square and Uber. I will also provide you with templates and cheat sheets that have really helped me in my career. In 2 hours, you can master product experimentation and immediately start applying it in your job or interviews . See you in the course!

Who this course is for:

Analytics or Data Science practitioners who want to master Product Experimentation or A/B Testing
Product Managers interested in learning A/B Testing
If you work in Product Development as a Product Manager, Engineer, Data Scientist or Analyst
If you are looking to be hired in big tech
If you are trying to break into data science
If you are looking to make a career switch into a role in Product Experimentation