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In 2021, 10 years after it burst on the scene, the MOOC ecosystem has reached 220M learners and 19.4K courses.
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Learn Statistics & Probability with free online courses and MOOCs from HKUST, UCT, Galileo University, Stanford and other top universities around the world. Read reviews to decide if a class is right for you.
Due to python’s simplicity and high readability, it is gaining its importance in the financial industry. The course combines both python coding and statistical concepts and applies into analyzing financial data, such as stock data.
If you’ve ever skipped over`the results section of a medical paper because terms like “confidence interval” or “p-value” go over your head, then you’re in the right place.
Usa estadística descriptiva e inferencial en los negocios. Aprende a tomar decisiones con ayuda de estimadores, análisis regresional y más.
Este curso en línea entrega al estudiante los conocimientos fundamentales de estadística para el análisis de datos, tanto a nivel personal como empresarial.
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University of Alberta
Black holes are fascinating and intriguing astronomical objects that capture our imagination. Astro 101, from University of Alberta, teaches us concepts such as astronomy, relativity, quantum physics, and much more.
University of California, San Diego
En esta Cohorte de 4 semanas, descubrirás invaluables técnicas de aprendizaje basadas en la neurociencia presentadas en el aclamado curso “Aprendiendo a Aprender” (Learning How to Learn) por Orlando Trejo, instructor del curso en Español.
Statistics is about extracting meaning from data. In this class, we will introduce techniques for visualizing relationships in data and systematic techniques for understanding the relationships using mathematics.
Learn some of the main tools used in statistical modeling and data science. We cover both traditional as well as exciting new methods, and how to use them in R.
Build foundational knowledge of data science with this introduction to probabilistic models, including random processes and the basic elements of statistical inference -- Part of the MITx MicroMasters program in Statistics and Data Science.
This course describes Bayesian statistics, in which one's inferences about parameters or hypotheses are updated as evidence accumulates. You will learn to use Bayes’ rule to transform prior probabilities into posterior probabilities, and be introduced to…
Increase your quantitative reasoning skills through a deeper understanding of probability and statistics.
Learn fundamental concepts in data analysis and statistical inference, focusing on one and two independent samples.
A focus on the techniques commonly used to perform statistical inference on high throughput data.
This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory d…
We have all heard the phrase “correlation does not equal causation.” What, then, does equal causation? This course aims to answer that question and more!
Over a period of 5 weeks, you will learn how causal effects are defined, what assumptions about…
Learn how to use R to implement linear regression, one of the most common statistical modeling approaches in data science.
In this course, we will expand our exploration of statistical inference techniques by focusing on the science and art of fitting statistical models to data. We will build on the concepts presented in the Statistical Inference course (Course 2) to emphasi…
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