R ProgrammingLinear RegressionStatistical Hypothesis TestingStatisticsLinear AlgebraConfidence IntervalBiostatistics
Advanced Statistics for Data Science Specialization
Familiarize yourself with fundamental concepts in probability and statistics, data analysis and linear models for Data Science.
Offered By
Advanced Statistics for Data Science SpecializationJohns Hopkins UniversityWhat 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.
Skills you will gain
About this Specialization
Fundamental concepts in probability, statistics and linear models are primary building blocks for data science work. Learners aspiring to become biostatisticians and data scientists will benefit from the foundational knowledge being offered in this specialization. It will enable the learner to understand the behind-the-scenes mechanism of key modeling tools in data science, like least squares and linear regression.
This specialization starts with Mathematical Statistics bootcamps, specifically concepts and methods used in biostatistics applications. These range from probability, distribution, and likelihood concepts to hypothesis testing and case-control sampling.
This specialization also linear models for data science, starting from understanding least squares from a linear algebraic and mathematical perspective, to statistical linear models, including multivariate regression using the R programming language. These courses will give learners a firm foundation in the linear algebraic treatment of regression modeling, which will greatly augment applied data scientists' general understanding of regression models.
This specialization requires a fair amount of mathematical sophistication. Basic calculus and linear algebra are required to engage in the content.
Applied Learning Project
The Advanced Statistics for Data Science Specialization incorporates a series of rigorous graded quizzes to test the understanding of key concepts such as probability, distribution, and likelihood concepts to hypothesis testing and case-control sampling.
Learner Career Outcomes
17%
Got a pay increase or promotion.
Shareable Certificate
Earn a Certificate upon completion
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Set and maintain flexible deadlines.
Advanced Level
This specialization requires a fair amount of mathematical sophistication. Basic calculus and linear algebra are required to engage in the content.
Approximately 5 months to complete
Suggested pace of 2 hours/week
English
Subtitles: English, Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, Spanish
Learner Career Outcomes
17%
Got a pay increase or promotion.
Shareable Certificate
Earn a Certificate upon completion
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Set and maintain flexible deadlines.
Advanced Level
This specialization requires a fair amount of mathematical sophistication. Basic calculus and linear algebra are required to engage in the content.
Approximately 5 months to complete
Suggested pace of 2 hours/week
English
Subtitles: English, Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, Spanish
There are 4 Courses in this Specialization
Mathematical Biostatistics Boot Camp 1
352 ratings
This class presents the fundamental probability and statistical concepts used in elementary data analysis. It will be taught at an introductory level for students with junior or senior college-level mathematical training including a working knowledge of calculus. A small amount of linear algebra and programming are useful for the class, but not required.
Mathematical Biostatistics Boot Camp 2
84 ratings
Learn fundamental concepts in data analysis and statistical inference, focusing on one and two independent samples.
Advanced Linear Models for Data Science 1: Least Squares
147 ratings
Welcome to the Advanced Linear Models for Data Science Class 1: Least Squares. This class is an introduction to least squares from a linear algebraic and mathematical perspective. Before beginning the class make sure that you have the following:
Advanced Linear Models for Data Science 2: Statistical Linear Models
66 ratings
Welcome to the Advanced Linear Models for Data Science Class 2: Statistical Linear Models. This class is an introduction to least squares from a linear algebraic and mathematical perspective. Before beginning the class make sure that you have the following:
Offered by
Johns Hopkins University
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
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