Introduction to the Tidyverse

Johns Hopkins University in Baltimore, founded in 1876, is a leading research university with a global reputation for excellence across medicine, public health, engineering, the arts and sciences. The university enrolls around 32,049 students, including approximately 5,233 international scholars, and offers an extensive portfolio of programs—about 238—across undergraduate, graduate and professional levels.

Johns Hopkins emphasizes research-led education, interdisciplinary collaboration and hands-on learning through labs, clinics and community partnerships. International students can access comprehensive support services for admissions, visas, academic advising and career development, and can participate in research opportunities, internships and global exchange programs that enhance professional prospects and real-world experience.

Baltimore’s urban setting provides access to vibrant cultural life, medical centers and industry partners, making it well suited for students interested in translational research and public service. The university’s strong alumni network, career services and industry links help graduates move into competitive roles worldwide, while campus resources support wellbeing, student activities and a diverse international community.

Introduction to the Tidyverse is a non-degree program at Johns Hopkins University for students who want to learn data science tools. It is an online program that lasts several weeks and is taught in English. This program introduces students to the Tidyverse, a powerful set of data science tools.

The curriculum covers tidy data, data transformation, and the data science project life cycle. Students learn about the Tidyverse ecosystem of R packages and how to use them for data import, tidying, exploration, visualization, and machine learning modeling. The program assumes familiarity with the R programming language.

Graduates can pursue careers as Data Scientists, Data Analysts, Business Intelligence Developers, Quantitative Analysts, or Data Engineers. They can work in various industries, including healthcare, finance, and technology, helping organizations make data-driven decisions and improve their operations.