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
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
About this Specialization
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.
This specialization requires a fair amount of mathematical sophistication. Basic calculus and linear algebra are required to engage in the content.
This specialization requires a fair amount of mathematical sophistication. Basic calculus and linear algebra are required to engage in the content.
There are 4 Courses in this Specialization
Mathematical Biostatistics Boot Camp 1
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
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
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
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.
Frequently Asked Questions
What is the refund policy?
Can I just enroll in a single course?
Is financial aid available?
Can I take the course for free?
Is this course really 100% online? Do I need to attend any classes in person?
Will I earn university credit for completing the Specialization?
More questions? Visit the Learner Help Center.