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
In data science, data is called "big" if it cannot fit into the memory of a single standard laptop or workstation. The analysis of big datasets requires using a cluster of tens, hundreds or... more
El futuro pertenece a la ciencia de datos y a quienes la entiendan. Al igual que el petróleo y el gas impulsaron las economías de los siglos XX y XXI, los datos impulsan cada vez mas la i... more
Thiscoursereviews the basic skills, concepts, and principles required to compile and disseminate macroeconomic and financial statistics. The course covers topics such as residence, institutional... more
Históricamente las matemáticas nacieron por primera vez, debido a la necesidad de entender nuestro entorno y tomar decisiones. En particular, la ciencia de datos (data science), se enfoca en el p... more
In this course, part of our Professional Certificate Program in Data Science,we cover several standard steps of the data wrangling process like importing data into R, tidying data, string... more
Powered by
