Principles of fMRI 1 (Coursera)

Principles of fMRI 1 (Coursera)

Functional Magnetic Resonance Imaging (fMRI) is the most widely used technique for investigating the living, functioning human brain as people perform tasks and experience mental states. It is a convergence point for multidisciplinary work from many disciplines. Psychologists, statisticians, physicists, computer scientists, neuroscientists, medical researchers, behavioral scientists, engineers, public health researchers, biologists, and others are coming together to advance our understanding of the human mind and brain. This course covers the design, acquisition, and analysis of Functional Magnetic Resonance Imaging (fMRI) data, including psychological inference, MR Physics, K Space, experimental design, pre-processing of fMRI data, as well as Generalized Linear Models (GLM’s).

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

Course 2 of 4 in the Neuroscience and Neuroimaging Specialization.

Syllabus

WEEK 1: This week we will introduce fMRI, and talk about data acquisition and reconstruction.
WEEK 2: This week we will discuss the fMRI signal, experimental design and pre-processing.
WEEK 3: This week we will discuss the General Linear Model (GLM).
WEEK 4: The description goes here

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Mathematical Biostatistics Boot Camp 1 (Coursera) Coursera
Johns Hopkins University

Mathematical Biostatistics Boot Camp 1 (Coursera)

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.

Jun 22nd 2026
4 Weeks
Effective Problem-Solving and Decision-Making (Coursera) Coursera
University of California, Irvine

Effective Problem-Solving and Decision-Making (Coursera)

Critical thinking – the application of scientific methods and logical reasoning to problems and decisions – is the foundation of effective problem solving and decision making. Critical thinking enables us to avoid common obstacles, test our beliefs and assumptions, and correct distortions in our thought processes. Gain confidence in assessing problems accurately, evaluating alternative solutions, and anticipating likely risks. Learn how to use analysis, synthesis, and positive inquiry to address individual and organizational problems and develop the critical thinking skills needed in today’s turbulent times. Using case studies and situations encountered by class members, explore successful models and proven methods that are readily transferable on-the-job.

Jun 22nd 2026
4 Weeks
Introduction to Probability and Data with R (Coursera) Coursera
Duke University

Introduction to Probability and Data with R (Coursera)

This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric summary statistics and basic data visualization.

Jun 22nd 2026
5-12 Weeks
Fundamentals of GIS (Coursera) Coursera
University of California, Davis

Fundamentals of GIS (Coursera)

Explore the world of spatial analysis and cartography with geographic information systems (GIS). What you will learn: define core geospatial concepts; practice with subset data using selections and feature attributes; create map books using advanced mapping techniques; create layer and map packages.

Jun 22nd 2026
4 Weeks
Experimentation for Improvement (Coursera) Coursera
McMaster University

Experimentation for Improvement (Coursera)

We are always using experiments to improve our lives, our community, and our work. Are you doing it efficiently? Or are you (incorrectly) changing one thing at a time and hoping for the best? In this course, you will learn how to plan efficient experiments - testing with many variables. Our goal is to find the best results using only a few experiments. A key part of the course is how to optimize a system.

Jun 22nd 2026
5-12 Weeks
Leadership Through Marketing (Coursera) Coursera
Northwestern University

Leadership Through Marketing (Coursera)

The success of every organization depends on attracting and retaining customers. Although the marketing concepts for doing so are well established, digital technology has empowered customers, while producing massive amounts of data, revolutionizing the processes through which organizations attract and retain customers. In this course, students will learn how to identify new opportunities to create value for empowered consumers, develop strategies that yield an advantage over rivals, and develop the data science skills to lead more effectively, allocate resources, and to confront this very challenging environment with confidence.

Jun 28th 2026
4 Weeks
Regression Models (Coursera) Coursera
Johns Hopkins University

Regression Models (Coursera)

Linear models, as their name implies, relates an outcome to a set of predictors of interest using linear assumptions. Regression models, a subset of linear models, are the most important statistical analysis tool in a data scientist’s toolkit. This course covers regression analysis, least squares and inference using regression models.

Jun 22nd 2026
4 Weeks
Market Research and Consumer Behavior (Coursera) Coursera
IE Business School

Market Research and Consumer Behavior (Coursera)

Your marketing quest begins here! The first course in this specialization lays the neccessary groundwork for an overall successful marketing strategy. It is separated into two sections: Market Research and Consumer Behavior. Gain the tools and techniques to translate a decision problem into a research question in the Market Research module. Learn how to design a research plan, analyze the data gathered and accurately interpret and communicate survey reports, translating the results into practical recommendations.

Jun 22nd 2026
4 Weeks
Linear Regression and Modeling (Coursera) Coursera
Duke University

Linear Regression and Modeling (Coursera)

This course introduces simple and multiple linear regression models. These models allow you to assess the relationship between variables in a data set and a continuous response variable. Is there a relationship between the physical attractiveness of a professor and their student evaluation scores? Can we predict the test score for a child based on certain characteristics of his or her mother? In this course, you will learn the fundamental theory behind linear regression and, through data examples, learn to fit, examine, and utilize regression models to examine relationships between multiple variables, using the free statistical software R and RStudio.

Jun 22nd 2026
4 Weeks
Big Data Modeling and Management Systems (Coursera) Coursera
University of California, San Diego

Big Data Modeling and Management Systems (Coursera)

Once you’ve identified a big data issue to analyze, how do you collect, store and organize your data using Big Data solutions? In this course, you will experience various data genres and management tools appropriate for each. You will be able to describe the reasons behind the evolving plethora of new big data platforms from the perspective of big data management systems and analytical tools.

Jun 22nd 2026
5-12 Weeks