Data science plays an important role in many industries. In facing massive amounts of heterogeneous data, scalable machine learning and data mining algorithms and systems have become extremely important for data scientists. The growth of volume, complexity and speed in data drives the need for scalable data analytic algorithms and systems. In this course, we study such algorithms and systems in the context of healthcare applications. In healthcare, large amounts of heterogeneous medical data hav...

# Course

Improvements in modern biology have led to a rapid increase in sensitivity and measurability in experiments and have reached the point where it is often impossible for a scientist alone to sort through the large volume of data that is collected from just one experiment. For example, individual data points collected from one gene expression study can easily number in the hundreds of thousands. These types of data sets are often referred to as ‘biological big data’ and require bioinformaticians to...

Using real-world examples from law, medicine and football, you’ll discover how data scientists make conclusions about unknowns based on the data available. Often, the data we have is incomplete, yet we’d still like to draw inferences about the world and quantify the uncertainty in our conclusions. This is called statistical inference. In this course, you will learn methods for statistical inference and see how to apply them to real-world data sets. The course will teach you estimation: given a r...

This course introduces the fundamentals of the field of sparse representations, starting with its theoretical concepts, and systematically presenting its key achievements. We will touch on theory and numerical algorithms. Modeling data is the way we – scientists – believe that information should be explained and handled. Indeed, models play a central role in practically every task in signal and image processing. Sparse representation theory puts forward an emerging, highly effective, and univers...

Capturing and analyzing data has changed how decisions are made and resources are allocated in businesses, journalism, government, and military and intelligence fields. Through better use of data, leaders are able to plan and enact strategies with greater clarity and confidence. Data drives increased organizational efficiency and a competitive advantage. Simply, analytics provide new insight and actionable intelligence. In education, the use of data and analytics to improve learning is referred ...

This course is part of the Microsoft Professional Program Certificate in Data Science. Learn what it takes to become a data scientist. This is the first stop in the Data Science curriculum from Microsoft. It will help you get started with the program, plan your learning schedule, and connect with fellow students and teaching assistants. Along the way, you’ll get an introduction to working with and exploring data using a variety of visualization, analytical, and statistical techniques. edX offers...

This course is part of the Microsoft Professional Program Certificate in Data Science. In this computer science course from Microsoft, developed in collaboration with the Technical University of Denmark (DTU), get the knowledge and skills you need to use R, the statistical programming language for data scientists, in the field of your choice. In this course you will learn all you need to get up to speed with programming in R. Explore R data structures and syntaxes, see how to read and write data...

This course is part of the Microsoft Professional Program Certificate in Data Science. This practical course, developed in partnership with Coding Dojo, targets individuals who have introductory level Python programming experience. The course teaches students how to start looking at data with the lens of a data scientist by applying efficient, well-known mining models in order to unearth useful intelligence, using Python, one of the popular languages for Data Scientists. Topics include data visu...

This course is part of the Microsoft Professional Program Certificate in Data Science and Microsoft Professional Program in Artificial Intelligence. Demand for data science talent is exploding. Develop your career as a data scientist, as you explore essential skills and principles with experts from Duke University and Microsoft. In this data science course, you will learn key concepts in data acquisition, preparation, exploration, and visualization taught alongside practical application oriented...

One of the principal responsibilities of a data scientist is to make reliable predictions based on data. When the amount of data available is enormous, it helps if some of the analysis can be automated. Machine learning is a way of identifying patterns in data and using them to automatically make predictions or decisions in the future. In this data science course, you will learn how basic concepts and elements of machine learning. The two main methods of machine learning you will learn are regre...

Use the R Programming Language to execute data science projects and become a data scientist. Implement business solutions, using machine learning and predictive analytics. The R language provides a way to tackle day-to-day data science tasks, and this course will teach you how to apply the R programming language and useful statistical techniques to everyday business situations. With this course, you'll be able to use the visualizations, statistical models, and data manipulation tools that modern...

The job of a data scientist is to glean knowledge from complex and noisy datasets. Reasoning about uncertainty is inherent in the analysis of noisy data. Probability and Statistics provide the mathematical foundation for such reasoning. In this course, part of the Data Science MicroMasters program, you will learn the foundations of probability and statistics. You will learn both the mathematical theory, and get a hands-on experience of applying this theory to actual data using Jupyter notebooks....

Use the R Programming Language to execute data science projects and become a data scientist. Implement business solutions, using machine learning and predictive analytics. The R language provides a way to tackle day-to-day data science tasks, and this course will teach you how to apply the R programming language and useful statistical techniques to everyday business situations. With this course, you'll be able to use the visualizations, statistical models, and data manipulation tools that modern...

In this course, part of our Professional Certificate Program in Data Science, you will learn valuable concepts in probability theory. The motivation for this course is the circumstances surrounding the financial crisis of 2007–2008. Part of what caused this financial crisis was that the risk of some securities sold by financial institutions was underestimated. To begin to understand this very complicated event, we need to understand the basics of probability. We will introduce important concepts...

Our capacity to collect and store data has exponentially increased, but deriving information from data from a scientific perspective requires a foundational knowledge of probability. Are you interested in a career in the emerging data science field, or as an actuarial scientist? Or want better to understand statistical theory and mathematical modeling? In this statistics and data analysis course, we will provide an introduction to mathematical probability to help meet your career goals in the ex...