Linear Algebra: Orthogonality and Diagonalization

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 in Linear Algebra, focusing on orthogonality and diagonalization, offered by Johns Hopkins University in the United States. It lasts several weeks and is taught in English. The main advantage is its application to AI and machine learning.

The curriculum covers orthogonal transformation, orthogonal bases, and symmetric matrices, linking algebraic properties with geometric equivalences. Students will develop skills in matrix analysis, which is crucial for interpreting, training, and using external data in AI and machine learning.

Upon completion, students can pursue careers as Data Scientists, Machine Learning Engineers, AI Researchers, Data Analysts, or Mathematicians, working in industries like technology, finance, or healthcare, for employers such as Google, Microsoft, or NASA.