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Introduction to Computational Thinking and Data Science
Description 6.00.2x will teach you how to use computation to accomplish a variety of goals and provides you with a brief introduction to a variety of topics in computational problem solving . This course is aimed at students with some prior programming experience in Python and a rudimentary knowledge of computational complexity. You will spend…
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Data Science Ethics
Description 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,…
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Data Science: Capstone
Description To become an expert data scientist you need practice and experience. By completing this capstone project you will get an opportunity to apply the knowledge and skills in R data analysis that you have gained throughout the series. This final project will test your skills in data visualization, probability, inference and modeling, data wrangling,…
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Data Science: Machine Learning
Description Perhaps the most popular data science methodologies come from machine learning. What distinguishes machine learning from other computer guided decision processes is that it builds prediction algorithms using data. Some of the most popular products that use machine learning include the handwriting readers implemented by the postal service, speech recognition, movie recommendation systems, and…
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Data Science: Linear Regression
Description Linear regression is commonly used to quantify the relationship between two or more variables. It is also used to adjust for confounding. This course, part ofourProfessional Certificate Program in Data Science, covers how to implement linear regression and adjust for confounding in practice using R. In data science applications, it is very common to…
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Data Science: Wrangling
Description In this course, part of our Professional Certificate Program in Data Science,we cover several standard steps of the data wrangling process like importing data into R, tidying data, string processing, HTML parsing, working with dates and times, and text mining. Rarely are all these wrangling steps necessary in a single analysis, but a data…
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Data Science: Productivity Tools
Description A typical data analysis project may involve several parts, each including several data files and different scripts with code. Keeping all this organized can be challenging. Part of our Professional Certificate Program in Data Science, this course explains how to use Unix/Linux as a tool for managing files and directories on your computer and…
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Data Science: Inference and Modeling
Description Statistical inference and modeling are indispensable for analyzing data affected by chance, and thus essential for data scientists. In this course, you will learn these key concepts through a motivating case study on election forecasting. This course will show you how inference and modeling can be applied to develop the statistical approaches that make…
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Data Science: Probability
Description 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…
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Data Science: Visualization
Description As part of our Professional Certificate Program in Data Science, this course covers the basics of data visualization and exploratory data analysis. We will use three motivating examples and ggplot2, a data visualization package for the statistical programming language R. We will start with simple datasets and then graduate to case studies about world…
