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...

# Course

As patients, we care about the privacy of our medical record; but as patients, we also wish to benefit from the analysis of data in medical records. As citizens, we want a fair trial before being punished for a crime; but as citizens, we want to stop terrorists before they attack us. As decision-makers, we value the advice we get from data-driven algorithms; but as decision-makers, we also worry about unintended bias. Many data scientists learn the tools of the trade and get down to work right a...

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...

Nowadays, image-based methods are indispensable for life scientists. Light microscopy especially, has evolved from sketched out observations by eye, to high throughput multi-plane, multi-channel, multi-position and multimode acquisitions that easily produce thousands of information-rich images that must be quantified somehow to answer biological questions. This course will teach you core concepts from image acquisition to image filtering and segmentation, to help you tackle simple image analys...

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...

Why do we study statistics? The field of statistics provides professionals and scientists with conceptual foundations and useful techniques for evaluating ideas, testing theories, and - ultimately - uncovering the truth in any situation. This course will familiarize you with data and basic statistical concepts, enabling you to analyze data using graphs and statistics. We'll start with types of data, controlled experiments, and observational study. You'll learn to use a histogram, a representatio...

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...

This course consists of an assessment that tests your knowledge on the course content from 14.310x - Data Analysis for Social Scientists, a statistics and data analysis course that will introduce you to the essential notions of probability and statistics. It will cover techniques in modern data analysis: estimation, regression and econometrics, prediction, experimental design, randomized control trials (and A/B testing), machine learning, and data visualization. It will illustrate these concepts...

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....