Statistical Methods for Computer Science

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.

This program is a Non-degree course called Statistical Methods for Computer Science, offered by Johns Hopkins University. It's for students and professionals in computer science and data science who want to develop advanced skills in probability and statistical modeling. The program lasts several weeks and helps you analyze complex data structures.

The curriculum covers essential topics like joint probability distributions, expectation, and simulation techniques. You'll also learn about exponential random graph models and probabilistic graphical models. The program includes hands-on experience with programming tools like R, which is widely used in the industry for statistical computing and graphics.

After completing this program, you can pursue roles like Data Analyst, Statistical Modeler, or Data Scientist. You can work in technology-driven environments, such as software development companies or research institutions. Other potential job titles include Business Intelligence Developer or Quantitative Analyst, where you'll apply your skills in data analysis, modeling, and interpretation to drive business decisions.