Data Science: Statistics and Machine Learning

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.

The Data Science: Statistics and Machine Learning program is a non-degree course offered by Johns Hopkins University. It's an online program that lasts several weeks and helps students build models, make inferences, and deliver interactive data products.

The curriculum covers statistical inference, regression models, machine learning, and data product development. Students apply their skills in a Capstone Project, building a data product with real-world data. This program is ideal for those who have already mastered data science fundamentals.

Graduates can pursue careers as Data Scientists, Machine Learning Engineers, or Data Analysts. They can work in various industries, including healthcare, finance, or technology, with employers like IBM, Microsoft, or Google.