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
Le « Big Data » et l'UX vous interpellent? Ce MOOC vous donnera les méthodes et outils pour analyser le spectre des données traitées en UX, de l'analyse qualitative aux analytiques Web. Vous appr... more
Decisions made by humans are rarely made by data alone. Human decision-makers have cognitive biases, are affected by emotions, and make conceptual leaps beyond what the data may suggest. The best... more
Data is everywhere, from the media to the health sciences, and from financial forecasting to engineering design. It drives our decisions, and shapes our views and beliefs. But how can we make sense... more
A majority of the world's data resides in databases. SQL (or Structured Query Language) is a powerful language for communicating with and extracting data from databases. A working knowledge of... more
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