Introduction to Computational Statistics for Data Scientists Specialization
Introduction to Computational Statistics for Data Scientists Specialization
Practical Bayesian Inference. A conceptual understanding of the techniques and the tools used to perform scalable Bayesian inference in practice with PyMC3.
Instructor: Dr. Srijith Rajamohan
Access provided by CalArts
2,892 already enrolled
3.9
(51 reviews)
Beginner level
Recommended experience
4 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
The basics of Bayesian modeling and inference.
A conceptual understanding of the techniques used to perform Bayesian inference in practice.
Learn how to use PyMC3 to solve real-world problems.
Skills you'll gain
- Probability
- Regression Analysis
- Sampling (Statistics)
- Statistical Modeling
- Python Programming
- Bayesian Statistics
- Probability Distribution
- Statistical Programming
- Databricks
- Simulations
- Jupyter
- Statistics
- Mathematical Software
- Predictive Modeling
- Statistical Analysis
- Classification And Regression Tree (CART)
- Statistical Inference
- Markov Model
- Data Science
- Statistical Machine Learning
Details to know
Shareable certificate
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Taught in English
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