Complete Course on A/B Testing with Interview Guide
What you'll learn
- How companies like Google, Facebook, Amazon use Experimentation to launch successful products
- Ace 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, 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
- You should have basic knowledge of statistical concepts such as mean, standard deviation and variance
Have you always wondered how companies like Google, Facebook, Amazon use experimentation and AB Testing to launch successful products?
Do you want to apply online 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, online controlled 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 AB 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 AB test
How to excel in AB testing interviews through real interview questions
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
There is a big shortage of courses that teach Data Science & Analytics in a way that is true to the technical depth but also marry business intuition & implementation really well. My courses address this problem and translate data science through the lens of business implementation, while going deep into the math. That means at the end of the course, not only will you master the mathematical concepts but you will also be ready to apply them in real world setting.
I have always been passionate about scientific thinking and deep analysis. My other passion is to teach and nurture. I bring these together as an instructor.
I have more than 12 years of experience in Data Science and Analytics working in Silicon Valley for most of those years. Over the years I have worked or consulted with companies such as Deloitte, SoFi, HP, Dell, Groupon, Walmart, Allstate and Mu Sigma.
I did MBA from Kellogg School of Management and Masters in Mathematics from Indian Institute of Technology (IIT) Kanpur.
I have headed many Marketing and Product Data Science & Analytics teams. In these roles I have helped launch and scale successful products and helped Marketing teams to optimize budgets of hundreds of millions of dollars through data science. Hired, mentored and promoted several managers, data scientists and analysts over the years.
My experience includes -
Experimentation and A/B testing across Product and Marketing, Multi-touch attribution, market mix modeling, LTV modeling, Customer segmentation, Machine learning models for targeted customer outreach and personalized campaign content/creative, Machine learning models to improve customer acquisition, engagement and retention, Business Intelligence