The objective of this course is to introduce Computational Statistics to aspiring or new data scientists. The attendees will start off by learning the basics of probability, Bayesian modeling and inference. This will be the first course in a specialization of three courses .Python and Jupyter notebooks will be used throughout this course to illustrate and perform Bayesian modeling. The course website is located at https://sjster.github.io/introduction_to_computational_statistics/docs/index.html. The course notebooks can be downloaded from this website by following the instructions on page https://sjster.github.io/introduction_to_computational_statistics/docs/getting_started.html.
This course is part of the Introduction to Computational Statistics for Data Scientists Specialization
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About this Course
Some experience with Data Science using the PyData Stack of NumPy, SciPy, Pandas, Scikit-learn.
Knowledge of Jupyter Notebooks will be beneficial.
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessWhat you will learn
The basics of Probability, Bayesian statistics, modeling and inference.
You will also get a hands-on introduction to using Python for computational statistics using Scikit-learn, SciPy and Numpy.
Skills you will gain
- Bayesian Inference
- visualization
- Python Programming
- Scipy
- Statistics
Some experience with Data Science using the PyData Stack of NumPy, SciPy, Pandas, Scikit-learn.
Knowledge of Jupyter Notebooks will be beneficial.
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessOffered by
Syllabus - What you will learn from this course
Environment Setup
Introduction to the Fundamentals of Probability
A Hands-On Introduction to Common Distributions
Sampling Algorithms
Reviews
- 5 stars38.70%
- 4 stars12.90%
- 3 stars25.80%
- 2 stars9.67%
- 1 star12.90%
TOP REVIEWS FROM INTRODUCTION TO BAYESIAN STATISTICS
Content/notes wise this course is great, But teaching style needs to be improved. Rather than reading the notes instructor should teach by giving examples and driving some of the results.
This course would be a bit hard for "complete" beginners, but would be enough for people who wish to refresh knowledge about Bayesian inference and stuff. The notes and codes are very good!!
About the Introduction to Computational Statistics for Data Scientists Specialization

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