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Harvard University

Data Science

Harvard University via edX Professional Certificate


The demand for skilled data science practitioners in industry, academia, and government is rapidly growing. The HarvardX Data Science program prepares you with the necessary knowledge base and useful skills to tackle real-world data analysis challenges. The program covers concepts such as probability, inference, regression, and machine learning and helps you develop an essential skill set that includes R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with Unix/Linux, version control with git and GitHub, and reproducible document preparation with RStudio.

In each course, we use motivating case studies, ask specific questions, and learn by answering these through data analysis. Case studies include: Trends in World Health and Economics, US Crime Rates, The Financial Crisis of 2007-2008, Election Forecasting, Building a Baseball Team (inspired by Moneyball), and Movie Recommendation Systems.

Throughout the program, we will be using the R software environment. You will learn R, statistical concepts, and data analysis techniques simultaneously. We believe that you can better retain R knowledge when you learn how to solve a specific problem.


Courses under this program:
Course 1: Data Science: R Basics

Build a foundation in R and learn how to wrangle, analyze, and visualize data.

Course 2: Data Science: Visualization

Learn basic data visualization principles and how to apply them using ggplot2.

Course 3: Data Science: Probability

Learn probability theory -- essential for a data scientist -- using a case study on the financial crisis of 2007-2008.

Course 4: Data Science: Inference and Modeling

Learn inference and modeling, two of the most widely used statistical tools in data analysis.

Course 5: Data Science: Productivity Tools

Keep your projects organized and produce reproducible reports using GitHub, git, Unix/Linux, and RStudio.

Course 6: Data Science: Wrangling

Learn to process and convert raw data into formats needed for analysis.

Course 7: Data Science: Linear Regression

Learn how to use R to implement linear regression, one of the most common statistical modeling approaches in data science.

Course 8: Data Science: Machine Learning

Build a movie recommendation system and learn the science behind one of the most popular and successful data science techniques.

Course 9: Data Science: Capstone

Show what you've learned from the Professional Certificate Program in Data Science.


Taught by

Rafael Irizarry

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