Courses

Introduction to Probability

Learn about basic probability The UC Berkeley Foundations of Data Science course combines three perspectives: inferential thinking, computational thinking, and real-world relevance.


Description

Learn about basic probability The UC Berkeley Foundations of Data Science course combines three perspectives: inferential thinking, computational thinking, and real-world relevance. Given data arising from some real-world phenomenon, how does one analyze that data so as to understand that phenomenon? The course teaches critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks. It delves into social issues surrounding data analysis such as privacy and design. Produced in partnership with the University of California, Berkeley - Ani Adhikari and John Denero with Contributions from David Wagner Computational and Inferential Thinking. In this module, you will learn: Fundamental Rules of Probability: Addition Rule, Multiplication Rule, and the Complement Rule. Important Probability Theory terms and concepts – Bayes' Rule, Prior & Posterior Probabilities, Errors, and Likelihoods – along with important mathematical notation. Update old predictions with new data and importance of keeping assumptions in mind as you make decisions.
Name Introduction to Probability
Language English
Duration 0:40 hours
Sector IT-ITES
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Price (INR) FREE
Availablity Available full time
Certification Availability from Knowledge Partner Not Available
Certification Availability from eSkillIndia Not Available
Assessment Availability from Knowledge Partner Available
Pre-Qualification 9th to 10th
NSQF level 7,7,7,7,7,4,4,4,7,7,7,7,7,7,5,6,6,7,8
FAQ URL https://docs.microsoft.com/en-us/learn/support/

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*   The QP alignment of the course is provided by the Knowledge Partner and the course may not cover the QP in entirety.