What will you learn in HarvardX: Data Science: R Basics course
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Understand the fundamentals of the R programming language for data science.
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Learn how to work with data types, variables, vectors, and data frames in R.
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Perform basic data manipulation and exploration using R.
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Write simple R scripts to analyze and summarize datasets.
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Understand how R fits into the broader data science workflow.
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Build a strong programming foundation for statistics, visualization, and machine learning in R.
Program Overview
Introduction to R and Programming Basics
⏳ 1–2 weeks
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Learn what R is and why it is widely used in data science.
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Understand the R environment, syntax, and basic commands.
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Work with variables, functions, and basic operations.
Data Types and Data Structures
⏳ 2–3 weeks
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Learn vectors, matrices, lists, and data frames.
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Understand how data is stored and accessed in R.
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Practice indexing and subsetting data efficiently.
Data Manipulation and Exploration
⏳ 2–3 weeks
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Perform basic data cleaning and transformation tasks.
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Summarize data using descriptive statistics.
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Explore datasets to identify patterns and anomalies.
Programming Practice for Data Science
⏳ 1–2 weeks
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Write reusable R code and simple functions.
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Understand common programming patterns used in data analysis.
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Prepare for advanced R-based courses in visualization, statistics, and machine learning.
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Job Outlook
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Essential foundation for Data Analysts, Data Scientists, and Researchers using R.
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Widely used in academia, healthcare, finance, and public policy.
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Strong prerequisite for advanced courses in statistical modeling and data visualization.
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Enhances analytical and programming confidence in data-driven roles.
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