Training schedule
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Deep Dive into Bayesian Modeling
Bayesian probability is a powerful technique that has revolutionized many industries by dealing with probability distributions in a different way. Discover techniques such as Markov chain Monte Carlo and Variational Inference, and how to solve multi-armed bandits. This 2-day training offers a deep-dive into this and much more!
This training is for you if…
You already have a good understanding of the basics of statistics.
You are interested in learning about Bayesian statistics and how it differs to the frequentist approach.
You want to solve real-world problems by translating them into probabilistic models.
This training is not for you if…
We also have a dedicated courses on A/B testing and innovating through statistical experiments.
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What you'll learn
You will learn:
- The theorem that underlies Bayesian data analysis and learn to apply it to solve probabilistic problems.
- How Bayes’ Theorem can be applied to data and make yourself comfortable with the Bayesian terminology: prior distributions, likelihoods, and posterior distributions.
- How The Bayesian paradigm is fundamentally different than the (more famous) “frequentist” paradigm.
- The (practical) pros and cons of working with either the Bayesian or the frequentist approach.
- Markov chain Monte Carlo (MCMC) methods
- How Variational inference offers an alternative to MCMC that is suitable to (very) big data.
The schedule
- Fundamentals: Bayes’ Theory
- From Bayes’ Theorem to Bayesian Data Analysis
- The Bayesian’ Paradigm
- Markov chain Monte Carlo with PyMC3
- Variational Inference: Big Data Bayesian Data Analysis
Multi-armed bandit problems (like for example A/B testing) can be solved by using Bayesian modeling. Participants will be presented with the simulation environment for Multi-armed bandits and encouraged to code a Bayesian decision-making algorithm. A perfect opportunity to creatively brainstorm and learn more about practical applications of Bayesian theory and effectively balancing the exploration-exploitation tradeoff
learning journey
Data Science Learning Journey
This Bayesian Modeling training is perfect for
- Data Scientists who know Machine Learning and want to learn about Bayesian statistics.
- This training is especially suited for Data Scientists who want to go beyond the standard probability theory.
- To get the most out of this training, we advise that you have at least one year of working experience with Python.
What will you learn during the Bayesian Modeling training:
- You will understand what makes Bayesian Probability so powerful, especially compared to the traditional frequentist approach.
- You will learn how to use the PyMC for building Bayesian models.
- We will also teach you how to apply Markov Chain Monte Carlo, Variational inference and other applications of Bayesian modeling in practice.