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Learn Statistical Inference online: university courses, full YouTube courses, and courses with free certificates, from the IITs, MIT, Harvard, Google, Microsoft and more.
Harvard University
Perform RNA-Seq, ChIP-Seq, and DNA methylation data analyses, using open source software, including R and Bioconductor.
Harvard University
A focus on several techniques that are widely used in the analysis of high-dimensional data.
Harvard University
The structure, annotation, normalization, and interpretation of genome scale assays.
Harvard University
A focus on the techniques commonly used to perform statistical inference on high throughput data.
Stanford Online
Stanford's "Introduction to Statistics" teaches you statistical thinking concepts that are essential for learning from data and communicating insights. By the end of the course, you will be able to perform exploratory data analysis, understand key principles of sampling, and select appropriate test…
Harvard University
An introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences.
Harvard University
Learn probability, an essential language and set of tools for understanding data, randomness, and uncertainty.
Harvard University
Learn advanced approaches to genomic visualization, reproducible analysis, data architecture, and exploration of cloud-scale consortium-generated genomic data.
Harvard University
Learn to use R programming to apply linear models to analyze data in life sciences.
Google
This is the third course in the Google Advanced Data Analytics Certificate. In this course, you’ll discover how data professionals use statistics to analyze data and gain important insights. You'll explore key concepts such as descriptive and inferential statistics, probability, sampling, confidenc…
Harvard University
Learn probability theory -- essential for a data scientist -- using a case study on the financial crisis of 2007-2008.
View the complete course: https://ocw.mit.edu/RES-6-012S18 Instructor: John Tsitsiklis, Patrick Jaillet The tools of probability theory, and of the related field of statistical inference, are the keys for being able to analyze and make sense of data. These tools underlie important advances in many…
MIT OpenCourseWare
This is a graduate-level introduction to the principles of statistical inference with probabilistic models defined using graphical representations. The material in this course constitutes a common foundation for work in machine learning, signal processing, artificial intelligence, computer vision,…
Duke University
This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data exa…
Johns Hopkins University
This course provides a framework for how analysts can create and evaluate quantitative measures. Consider the many tricky concepts that are often of interest to analysts, such as health, educational attainment and trust in government. This course will explore various approaches for quantifying thes…
The University of Texas at Austin
Use R to learn fundamental statistical topics such as descriptive statistics and modeling.
MITx
Master the probabilistic reasoning and statistical inference that machine learning is built on. Part two in a five-part series, this online course teaches discrete modeling skills that form the foundation of classification, prediction, and data analysis.
MITx
Master the probabilistic reasoning and statistical inference that machine learning is built on. Part one in a five-part series, this online course explores the foundations of data analysis.
MITx
Master the probabilistic reasoning and statistical inference that machine learning is built on. Part five of a five-part series, this online course teaches you how to test hypotheses and choose the right machine learning models for deployment.
MITx
Master the probabilistic reasoning and statistical inference that machine learning is built on. Part four in a five-part series, this online course teaches you how to quantify uncertainty and make data-driven decisions.
