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
Statistics 2 Part 1 is a self-paced course from LSE which aims to develop your knowledge of elementary statistical theory, particularly relating to the concepts, methods and techniques of... more
What makes a good business decision? How can we combine effective data analytics and feed robust foresight and scenario planning processes? We need to rethink the organization, and see it as... more
Discover practical ways to critically appraise scientific literature, including the conduction and interpretation of systematic reviews and meta-analyses. Additionally, you will learn how to... 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
En este curso de análisis e interpretación de datos te presentaremos técnicas avanzadas de importación de datos y estrategias diversas para consolidarlos y prepararlos una vez importados de for... more
Powered by
