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
Please Note: Learners who successfully complete this IBM course can earn a skill badge — a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in thi... more
Demystify complex big data technologies Compared to traditional data processing, modern tools can be complex to grasp. Before we can use these tools effectively, we need to know how to handle big... 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
We are all getting familiar with the image of a drone in the sky. Although flying a drone is fun, drones are not toys. More and more UAVs or drones are used by governments and companies to gain... more
We begin with an introduction to the relevant biology, explaining what we measure and why. Then we focus on the two main measurement technologies: next generation sequencing and microarrays. We... more
Powered by
