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Learner Reviews & Feedback for Probability Foundations for Data Science and AI by University of Colorado Boulder
257 ratings
About the Course
Understand the foundations of probability and its relationship to statistics and data science. We’ll learn what it means to calculate a probability, independent and dependent outcomes, and conditional events. We’ll study discrete and continuous random variables and see how this fits with data collection. We’ll end the course with Gaussian (normal) random variables and the Central Limit Theorem and understand its fundamental importance for all of statistics and data science.
This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) and the Master of Science in Artificial Intelligence (MS-AI) degrees offered on the Coursera platform. These interdisciplinary degrees bring together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the CU degrees on Coursera are ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics.
Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.
Learn more about the MS-AI program at https://www.coursera.org/degrees/ms-artificial-intelligence-boulder
Logo adapted from photo by Christopher Burns on Unsplash.
Top reviews
TQ
Mar 4, 2023
This course taught me the basics of probability, R programming, and Latex. I am deeply grateful to Prof. Anne Dougherty, UC Boulder, and Coursera for this tough but wonderful experience.
MB
Jun 15, 2022
This is a great course on probability. Although I felt like it was too easy and should include more PDFs (such as Beta and Gamma) and random variable transformations.
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