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Applied Statistics in Python

Updated 05/2026
Explore Python-based statistical analysis to gain essential decision-making skills such as A/B testing and Bayesian models.
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PythonProbability & Statistics16 hr4,440

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Track Description

Applied Statistics in Python

Dive into the world of Python-based statistical analysis with this comprehensive track designed to equip you with the essential skills to make data-driven decisions. With its user-friendly syntax and robust libraries, Python has become a favorite tool for data scientists and statisticians. Whether it’s improving business strategies with A/B testing, drawing conclusions from companies' data, or developing probabilistic models in Bayesian frameworks, you will be well-prepared to tackle challenges in any industry. Start this track today to elevate your capabilities and become a critical contributor to any data-centric team.

Prerequisites

There are no prerequisites for this track

  • Course

    1

    Experimental Design in Python

    Implement experimental design setups and perform robust statistical analyses to make precise and valid conclusions!

  • Course

    2

    A/B Testing in Python

    Learn the practical uses of A/B testing in Python to run and analyze experiments. Master p-values, sanity checks, and analysis to guide business decisions.

Applied Statistics in Python
4 Courses
Track
Complete

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