Search result for Courses taught by Michael Love
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Statistics and R
by Rafael Irizarry , Michael Love- 0.0
4 Weeks
An introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences. This course teaches the R programming language in the context of statistical data and statistical analysis in the life sciences. We provide R programming examples in a way that will help make the connection between concepts and implementation....
$249
High-Dimensional Data Analysis
by Rafael Irizarry , Michael Love- 0.0
4 Weeks
A focus on several techniques that are widely used in the analysis of high-dimensional data. If you’re interested in data analysis and interpretation, then this is the data science course for you. Specifically, we will describe the principal component analysis and factor analysis and demonstrate how these concepts are applied to data visualization and data analysis of high-throughput experimental data....
$149
Statistical Inference and Modeling for High-throughput Experiments
by Rafael Irizarry , Michael Love- 0.0
4 Weeks
A focus on the techniques commonly used to perform statistical inference on high throughput data. In this course you’ll learn various statistics topics including multiple testing problem, error rates, error rate controlling procedures, false discovery rates, q-values and exploratory data analysis. We then introduce statistical modeling and how it is applied to high-throughput data....
$149
Introduction to Bioconductor
by Rafael Irizarry , Michael Love , Vincent Carey- 0.0
4 Weeks
The structure, annotation, normalization, and interpretation of genome scale assays. We begin with an introduction to the relevant biology, explaining what we measure and why. Then we focus on the two main measurement technologies: next generation sequencing and microarrays. Given the diversity in educational background of our students we have divided the series into seven parts....
$149
Case Studies in Functional Genomics
by Rafael Irizarry , Michael Love , Vincent Carey- 0.0
5 Weeks
Perform RNA-Seq, ChIP-Seq, and DNA methylation data analyses, using open source software, including R and Bioconductor. We will explain how to perform the standard processing and normalization steps, starting with raw data, to get to the point where one can investigate relevant biological questions. We start with RNA-seq data analysis covering basic concepts and a first look at FASTQ files....
$149
Advanced Bioconductor
by Rafael Irizarry , Michael Love- 0.0
4 Weeks
Learn advanced approaches to genomic visualization, reproducible analysis, data architecture, and exploration of cloud-scale consortium-generated genomic data. In this course, we begin with approaches to visualization of genome-scale data, and provide tools to build interactive graphical interfaces to speed discovery and interpretation. Multiomic data integration is illustrated using a curated version of The Cancer Genome Atlas....
$149
Introduction to Linear Models and Matrix Algebra
by Rafael Irizarry , Michael Love- 0.0
4 Weeks
Learn to use R programming to apply linear models to analyze data in life sciences. 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....
$149
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Course Definition & Meaning - Merriam-Webster
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course: [noun] the act or action of moving in a path from point to point....
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