Probability and Statistics in Data Science using Python
About this Course
The job of a data scientist is to glean knowledge from complex and noisy datasets. Reasoning about uncertainty is inherent in the analysis of noisy data. Probability and Statistics provide the mathematical foundation for such reasoning. In this course, part of the Data Science MicroMasters program, you will learn the foundations of probability and statistics. You will learn both the mathematical theory, and get a hands-on experience of applying this theory to actual data using Jupyter notebooks. Concepts covered included: random variables, dependence, correlation, regression, PCA, entropy and MDL.Created by: The University of California, San Diego
Level: Advanced
Related Online Courses
As part of our Professional Certificate Program in Data Science, this course covers the basics of data visualization and exploratory data analysis. We will use three motivating examples and... more
El análisis exploratorio de datos (EDA, por sus siglas en inglés, Exploratory Data Analysis) es el proceso o tratamiento estadístico al cual se someten los datos de una muestra con la que se bu... more
Advanced Bayesian Data Analysis Using R is part two of the Bayesian Data Analysis in R professional certificate. This course is directed at people who are already familiar with the fundamentals of... more
Perhaps the most popular data science methodologies come from machine learning. What distinguishes machine learning from other computer guided decision processes is that it builds prediction... more
In the information age, data is all around us. Within this data are answers to compelling questions across many societal domains (politics, business, science, etc.). But if you had access to a... more
Powered by
