Familiarize yourself with fundamental concepts in probability and statistics, data analysis and linear models for Data Science.

4.5

stars

99 ratings

Brian Caffo, PhD

9,932 already enrolled

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Advanced Statistics for Data Science SpecializationJohns Hopkins University

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.

Skills you will gain

R ProgrammingLinear RegressionStatistical Hypothesis TestingStatisticsLinear AlgebraConfidence IntervalBiostatistics

About this Specialization

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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

How the Specialization Works

Take Courses

A Coursera Specialization is a series of courses that helps you master a skill. To begin, enroll in the Specialization directly, or review its courses and choose the one you'd like to start with. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. It’s okay to complete just one course — you can pause your learning or end your subscription at any time. Visit your learner dashboard to track your course enrollments and your progress.

Hands-on Project

Every Specialization includes a hands-on project. You'll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you'll need to finish each of the other courses before you can start it.

Earn a Certificate

When you finish every course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.

There are 4 Courses in this Specialization

Course1

Course 1

Mathematical Biostatistics Boot Camp 1

4.5

stars

375 ratings

•

81 reviews

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.

Course2

Course 2

Mathematical Biostatistics Boot Camp 2

4.4

stars

98 ratings

•

20 reviews

Learn fundamental concepts in data analysis and statistical inference, focusing on one and two independent samples.

Course3

Course 3

Advanced Linear Models for Data Science 1: Least Squares

4.4

stars

156 ratings

•

39 reviews

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:

- A basic understanding of linear algebra and multivariate calculus. - A basic understanding of statistics and regression models. - At least a little familiarity with proof based mathematics. - Basic knowledge of the R programming language. After taking this course, students will have a firm foundation in a linear algebraic treatment of regression modeling. This will greatly augment applied data scientists' general understanding of regression models.

Course4

Course 4

Advanced Linear Models for Data Science 2: Statistical Linear Models

4.6

stars

69 ratings

•

12 reviews

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:

Instructor

Brian Caffo, PhD

Professor, Biostatistics

Bloomberg School of Public Health

1,363,572 Learners

29 Courses

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.

Frequently Asked Questions

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Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.
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Is this course really 100% online? Do I need to attend any classes in person?
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
Will I earn university credit for completing the Specialization?
This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more. Online Degrees and Mastertrack™ Certificates on Coursera provide the opportunity to earn university credit.

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