Advanced Statistics for Data Science Specialization

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Course Features

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Duration

5 months

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Advanced

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Effort

2 hours per week

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Teaching Type

Self Paced

Course Description

Data science is built upon fundamental concepts in statistics, probability, and linear modeling. This specialization will provide the foundational knowledge necessary to help students become data scientists and biostatisticians. This specialization will allow the learner to gain an understanding of the workings of data science tools such as least squares or linear regression. This specialization begins with Mathematical Statistics bootcamps. It focuses on concepts and methods used for biostatistics applications. These include probability, distribution, likelihood concepts, hypothesis testing, and case-control sampling. This specialization includes linear models for data science. It covers understanding least squares from both a mathematical and linear algebraic perspective to statistical linear models using R programming language. These courses will provide a solid foundation in linear algebraic regression modeling. This will enhance the knowledge of applied data scientists about regression models. This specialization requires some mathematical proficiency. To engage in this content, you will need to know basic calculus and linear algebra.

Course Overview

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International Faculty

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Post Course Interactions

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Instructor-Moderated Discussions

Skills You Will Gain

What You Will Learn

Learn about probability, expectations, conditional probabilities, distributions, confidence intervals, bootstrapping, binomial proportions, and more

Understand the matrix algebra of linear regression models

Learn about canonical examples of linear models to relate them to techniques that you may already be using

Course Instructors

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Brian Caffo, PhD

Professor, Biostatistics

Brian Caffo, PhD is a professor in the Department of Biostatistics at the Johns Hopkins University Bloomberg School of Public Health. He graduated from the Department of Statistics at the University ...
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