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Online Course

Introduction to Linear Models and Matrix Algebra

Harvard University via edX

Overview

Matrix Algebra underlies many of the current tools for experimental design and the analysis of high-dimensional data. In this introductory online course in data analysis, we will use matrix algebra to represent the linear models that commonly used to model differences between experimental units. We perform statistical inference on these differences. Throughout the course we will use the R programming language to perform matrix operations.

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. Note that the statistics and programming aspects of the class ramp up in difficulty relatively quickly across the first three courses. You will need to know some basic stats for this course. By the third course will be teaching advanced statistical concepts such as hierarchical models and by the fourth advanced software engineering skills, such as parallel computing and reproducible research concepts.

These courses make up two Professional Certificates and are self-paced:

Data Analysis for Life Sciences:

  • PH525.1x: Statistics and R for the Life Sciences
  • PH525.2x: Introduction to Linear Models and Matrix Algebra
  • PH525.3x: Statistical Inference and Modeling for High-throughput Experiments
  • PH525.4x: High-Dimensional Data Analysis

Genomics Data Analysis:

  • PH525.5x: Introduction to Bioconductor
  • PH525.6x: Case Studies in Functional Genomics
  • PH525.7x: Advanced Bioconductor

This class was supported in part by NIH grant R25GM114818.

Taught by

Michael Love and Rafael Irizarry

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Reviews

4.4 rating, based on 11 reviews

Start your review of Introduction to Linear Models and Matrix Algebra

  • Brandt Pence completed this course, spending 2 hours a week on it and found the course difficulty to be easy.

    (Note, I took these courses before the recent reorganization. I believe the material for the first few courses is the same, so my comments should still be valid.) This is the second PH525 sequence course offered through HarvardX. Most of the course...
  • Sepehr Setayesh

    Sepehr Setayesh is taking this course right now.

    I'm so excited to take this class and I hope to be useful for me in future . Please keep this courses free for others.
    Thanks
  • Anonymous

    Anonymous is taking this course right now.

    at some point before 2 weeks since starting the course, I was @ 4th week of the course and the session ended... I am not sure if I will be allowed to continue or will have to re-take this course. I wish there was a display for End dates of each session. In...
  • Profile image for David Chen
    David Chen

    David Chen completed this course, spending 5 hours a week on it and found the course difficulty to be hard.

    This was one of the first MOOC courses I've taken, back when platforms such as edX and Coursera were just becoming popular. I remembered struggling a lot with this course, but the videos and exercises were very informative, and guided me towards understanding basic linear algebra and application of linear model and statistical tests to biological data sets. Since then, I have recommended this data to many students especially those who are getting started with data analysis.
  • Vlad Podgurschi completed this course, spending 5 hours a week on it and found the course difficulty to be medium.

  • Alun Ap Rhisiart

    Alun Ap Rhisiart is taking this course right now.

  • Dennis B. Mendiola

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