Free Online Course on Introduction to Linear Models and Matrix Algebra

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Harvard University is offering free online course on Introduction to Linear Models and Matrix Algebra. In this introductory data analysis course, University will use matrix algebra to represent the linear models that commonly used to model differences between experimental units.

In this four week course, applicants will learn to use R programming to apply linear models to analyze data in life sciences. This course will start on July 1, 2017.

Course At A Glance 

Length: 4 weeks
Effort: 2-4 hours pw
Subject: Biology & Life Sciences
Institution: Harvard University and edx
Languages: English
Price: Free
Certificate Available: Yes, Add a Verified Certificate for $49
Session: Course Starts on July 1, 2017

Providers’ Details

Harvard University is devoted to excellence in teaching, learning, and research, and to developing leaders in many disciplines who make a difference globally. Harvard faculty are engaged with teaching and research to push the boundaries of human knowledge.

About This Course

Given the diversity in educational background of our students we have divided the series into seven parts. You can take the entire series or individual courses that interest you. If you are a statistician you should consider skipping the first two or three courses, similarly, if you are biologists you should consider skipping some of the introductory biology lectures.

Why Take This Course?

Matrix Algebra underlies many of the current tools for experimental design and the analysis of high-dimensional data.

Learning Outcomes

  • Matrix algebra notation
  • Matrix algebra operations
  • Application of matrix algebra to data analysis
  • Linear models
  • Brief introduction to the QR decomposition

Instructors

Rafael Irizarry

Rafael Irizarry is a Professor of Biostatistics at the Harvard T.H. Chan School of Public Health and a Professor of Biostatistics and Computational Biology at the Dana Farber Cancer Institute. For the past 15 years, Dr. Irizarry’s research has focused on the analysis of genomics data.

Michael Love

Michael Love is a postdoctoral fellow with Dr. Irizarry in the Department of Biostatistics at the Dana Farber Cancer Institute and Harvard T.H. Chan School of Public Health.

Requirements

  • Basic math
  • Basic stats and R programming or PH525.1x

How To Join This Course

  • Go to the course website link
  • Create an edX account to SignUp
  • Choose “Register Now” to get started.
  • EdX offers honor code certificates of achievement, verified certificates of achievement, and XSeries certificates of achievement. Currently, verified certificates are only available in some courses.
  • Once applicant sign up for a course and activate their account, click on the Log In button on the edx.org homepage and type in their email address and edX password. This will take them to the dashboard, with access to each of their active courses. (Before a course begins, it will be listed on their dashboard but will not yet have a “view course” option.)

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