Data Science Decisions in Time:Sequential Hypothesis Testing Online Course

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.

Data Science Decisions in Time is a non-degree online course for students who want to learn about sequential hypothesis testing. It's taught in English and lasts several weeks. A key advantage is that it's online, so you can learn from anywhere.

The curriculum covers specific subjects like data analysis and testing methods. You'll develop skills in data interpretation and decision-making. The course includes hands-on components to help you practice what you learn.

After completing this course, you can pursue jobs like Data Analyst, Business Intelligence Developer, or Quantitative Analyst. You can work in industries such as finance, healthcare, or technology for employers like research institutions or private companies.