EdX

Biostatistics for Big Data Applications (edX)

Offered by University of Texas Medical Branch,
Biostatistics for Big Data Applications (edX)

Learn data analysis basics for working with biomedical big data with practical hands-on examples using R. This course provides a broad foundation of statistical terms and concepts as well as an introduction to the R statistical software package. The topics covered are fundamental components of biostatistical methods used in both omics and population health research.

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

Working with biomedical big data presents many challenges; familiarity with common statistical terms and definitions, and understanding basic statistical theory will help you overcome those challenges.
Topic-specific information and examples will be followed by self-assessment opportunities for you to gauge your understanding. In addition, practice datasets and exercises will be provided for you to improve your R programming skills.

What you'll learn:

  • Basic R Programming
  • How to create and interpret graphical summaries of data
  • Basic inferential statistics including parametric and nonparametric methods
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Computational Thinking and Big Data (edX) EdX
University of Adelaide,AdelaideX

Computational Thinking and Big Data (edX)

CS: Software Engineering Statistics & Data Analysis

Learn the core concepts of computational thinking and how to collect, clean and consolidate large-scale datasets. Computational thinking is an invaluable skill that can be used across every industry, as it allows you to formulate a problem and express a solution in such a way that a computer can effectively carry it out.

Self Paced
Self-Paced
Big Data Data Science Algorithmic Thinking
Details
Introduction to Linear Models and Matrix Algebra (edX) EdX
HarvardX,Harvard University

Introduction to Linear Models and Matrix Algebra (edX)

Sci: Biology & Life Sciences Statistics & Data Analysis

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 data analysis course, 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.

Self Paced
Self-Paced
Algebra Linear Algebra Matrix
Details
Unix Tools: Data, Software and Production Engineering (edX) EdX
Delft University of Technology,DelftX

Unix Tools: Data, Software and Production Engineering (edX)

Computer Science

Grow from being a Unix novice to Unix wizard status! Process big data, analyze software code, run DevOps tasks and excel in your everyday job through the amazing power of the Unix shell and command-line tools. Processing information is the hallmark of all modern organizations, which are increasingly digital: absorbing, processing and generating information is a key element of their business.

Self Paced
Self-Paced
Data Software Engineering Unix
Details
Introduction to Digital Humanities (edX) EdX
HarvardX,Harvard University

Introduction to Digital Humanities (edX)

Humanities Computer Science

Develop skills in digital research and visualization techniques across subjects and fields within the humanities. This course will show you how to manage the many aspects of digital humanities research and scholarship. Whether you are a student or scholar, librarian or archivist, museum curator or public historian — or just plain curious — this course will help you bring your area of study or interest to new life using digital tools.

Self Paced
Self-Paced
Data Analysis Command Line Interface Digital Humanities
Details
Statistics and R (edX) EdX
HarvardX,Harvard University

Statistics and R (edX)

Sci: Biology & Life Sciences Statistics & Data Analysis

An introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences. We will learn the basics of statistical inference in order to understand and compute p-values and confidence intervals, all while analyzing data with R. We provide R programming examples in a way that will help make the connection between concepts and implementation.

Self Paced
Self-Paced
Statistics Data Analysis Statistical Inference
Details
Programming for Data Science (edX) EdX
University of Adelaide,AdelaideX

Programming for Data Science (edX)

CS: Programming Data Science

Learn how to apply fundamental programming concepts, computational thinking and data analysis techniques to solve real-world data science problems. There is a rising demand for people with the skills to work with Big Data sets and this course can start you on your journey through our Big Data MicroMasters program towards a recognised credential in this highly competitive area. Using practical activities you will learn how digital technologies work and will develop your coding skills through engaging and collaborative assignments.

Self Paced
Self-Paced
Programming Big Data Data Analysis
Details
Big Data Capstone Project (edX) EdX
University of Adelaide,AdelaideX

Big Data Capstone Project (edX)

Statistics & Data Analysis Data Science

Further develop your knowledge of big data by applying the skills you have learned to a real-world data science project. This project will give you the opportunity to deepen your learning by giving you valuable experience in evaluating, selecting and applying relevant data science techniques, principles and theory to a data science problem. This project will see you plan and execute a reasonably substantial project and demonstrate autonomy, initiative and accountability.

Self Paced
Self-Paced
Big Data Data Science Data Analytics
Details
Analyzing and Visualizing Data with Power BI (edX) EdX
Davidson College,DavidsonX

Analyzing and Visualizing Data with Power BI (edX)

Statistics & Data Analysis Computer Science

Step up your analytics game and learn one of the most in-demand job skills in the United States. Power BI is a robust business analytics and visualization tool from Microsoft that helps data professionals bring their data to life and tell more meaningful stores. This four-week course is a beginner's guide to working with data in Power BI and is perfect for professionals. You'll become confident in working with data, creating data visualizations, and preparing reports and dashboards.

Self Paced
Self-Paced
Data Analysis Data Visualization Power BI
Details
High-Dimensional Data Analysis (edX) EdX
HarvardX,Harvard University

High-Dimensional Data Analysis (edX)

Sci: Biology & Life Sciences Statistics & Data Analysis

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. We start by learning the mathematical definition of distance and use this to motivate the use of the singular value decomposition (SVD) for dimension reduction and multi-dimensional scaling and its connection to principle component analysis.

Self Paced
Self-Paced
Machine Learning Clustering Data Analysis
Details
Excel avanzado: importación y análisis de datos (edX) EdX
Universitat Politècnica de València,UPValenciaX

Excel avanzado: importación y análisis de datos (edX)

CS: Information & Technology Statistics & Data Analysis

Conoce técnicas y estrategias avanzadas para importar, consolidar y visualizar con Excel datos provenientes de cualquier fuente. En este curso de análisis e interpretación de datos te presentaremos técnicas avanzadas de importación de datos y estrategias diversas para consolidarlos y prepararlos una vez importados de forma que puedas extraer las conclusiones que necesitas (basadas en nuestra experiencia en el uso de Microsoft Excel y demostradas con casos reales).

Self Paced
Self-Paced
Excel Microsoft Big Data
Details