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
Este curso se dirige a usuarios de Tableau que han madurado un sólido conocimiento del software en los cursos de nivel básico e intermedio. En los precedentes módulos, hemos podido aprender a an... 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, gain experience in data visualization and cloud technologies to support business analytics. In the first half of the course, create and share compelling data visualizations to... more
In autonomous vehicles such as self-driving cars, we find a number of interesting and challenging decision-making problems. Starting from the autonomous driving of a single vehicle, to the... more
Use Tableau to explore data and discover insights to innovate data-driven decision-making. Employer demand for Tableau skills will grow 35% over the next 10 years. Whether you are in a... more
Powered by
