{"id":27966,"date":"2026-09-03T15:28:44","date_gmt":"2026-09-03T13:28:44","guid":{"rendered":"https:\/\/semmelweis.hu\/emk\/?page_id=27966"},"modified":"2026-09-03T16:18:01","modified_gmt":"2026-09-03T14:18:01","slug":"data-science-in-health-msc","status":"publish","type":"page","link":"https:\/\/semmelweis.hu\/emk\/en\/education\/data-science-in-health-msc\/","title":{"rendered":"Data Science in Health (MSc)"},"content":{"rendered":"<h2>Training Objective<\/h2>\n<p style=\"text-align: justify\">To train a group of professionals with innovative skills who can participate in solving problems related to preserving and restoring human health, or preventing the deterioration of chronic conditions, using modern data science approaches. Our expert team aims to ensure that data-driven healthcare and artificial intelligence<br \/>\nsolutions evolve into system-level capabilities in Hungary.<\/p>\n<h2>Training Program<\/h2>\n<div class=\"fontos_div\">\n<p><strong>Name of the master\u2019s program:<\/strong> <em><strong>Data Science in Health.<\/strong><\/em> <br \/>\nA 120-credit master\u2019s program, launched for the first time in autumn 2024.<br \/>\n<strong>Mode of study:<\/strong> part-time, correspondence.<br \/>\n<strong>Degree awarded: <em>Data Scientist in Health.<\/em><\/strong><br \/>\n<strong>Funding:<\/strong> state-funded and self-funded study options.<br \/>\n<strong>Self-funded tuition fee:<\/strong> HUF 780 000 per semester.<br \/>\n<strong>Duration:<\/strong> four semesters.<br \/>\n<strong>Teaching schedule:<\/strong> Classes are delivered in subject-based blocks on pre-<br \/>\nscheduled weekdays, from 9:00 to 16:00.<br \/>\n<strong>Language: The program is delivered exclusively in Hungarian.<\/strong><br \/>\n<strong>Location:<\/strong> Education takes place in the building of the Semmelweis University Faculty of Health and Public Services Health Services Management Training Centre located in Budapest (1125 <strong>Budapest<\/strong>, K\u00fatv\u00f6lgyi \u00fat 2.).<\/p>\n<\/div>\n<h2>Program Description<\/h2>\n<p style=\"text-align: justify\">Graduates of the program acquire innovative skills applicable in both public and private healthcare. These skills are essential for analyzing, interpreting, planning, and evaluating health interventions, healthcare programs, services, and practices using data-driven methods. Graduates will be able to design, implement, and operate data processing, analytical, and decision-support systems tailored to specific health-<br \/>\nrelated problems.<\/p>\n<p style=\"text-align: justify\">The program supports the development of these skills through a predominantly practice-oriented curriculum, combining data-driven healthcare expertise with IT and mathematical knowledge.<\/p>\n<p style=\"text-align: justify\">A key component of the program is the practical training, including lab-based project work, during which participants examine data-driven solutions to complex healthcare problems.<\/p>\n<h2 style=\"text-align: justify\">Target Group<\/h2>\n<h2 style=\"text-align: justify\"><span style=\"color: #1e2326;font-family: 'PT serif', serif;font-size: 1rem;font-weight: 400\">We welcome physicians, pharmacists, healthcare professionals, IT specialists, and <\/span><span style=\"color: #1e2326;font-family: 'PT serif', serif;font-size: 1rem;font-weight: 400\">data scientists who wish to contribute to shaping data-driven healthcare. <\/span><span style=\"color: #1e2326;font-family: 'PT serif', serif;font-size: 1rem;font-weight: 400\">The program integrates health science, mathematics, and informatics knowledge, and <\/span><span style=\"color: #1e2326;font-family: 'PT serif', serif;font-size: 1rem;font-weight: 400\">primarily expects applicants with backgrounds in medical and health sciences, <\/span><span style=\"color: #1e2326;font-family: 'PT serif', serif;font-size: 1rem;font-weight: 400\">informatics, or natural sciences. However, it also offers an excellent opportunity for <\/span><span style=\"color: #1e2326;font-family: 'PT serif', serif;font-size: 1rem;font-weight: 400\">graduates from other fields &#8211; such as law or economics &#8211; to expand their knowledge.<\/span><\/h2>\n<h2 style=\"text-align: justify\">Training Objectives<\/h2>\n<p style=\"text-align: justify\">\u2022 Building professional competencies and human capacity to support the development of data-driven healthcare through specialized data science education.<br \/>\n\u2022 Breaking down the silos between medical\/health and IT\/data science professions, facilitating effective collaboration.<br \/>\n\u2022 Supporting the practical application of data science and artificial intelligence in healthcare.<br \/>\n\u2022 Enabling the solution of real-world problems during the training.<br \/>\n\u2022 Preparing graduates for continuing their studies in doctoral programmes.<\/p>\n<div class=\"fontos_div w-100\">\n<p style=\"text-align: justify\"><strong>Programme Director: <\/strong>Dr Tam\u00e1s Jo\u00f3<\/p>\n<p style=\"text-align: justify\"><strong>Programme Coordinator:<\/strong><br \/>\nRita K\u00f3r\u00f3di<br \/>\nEmail: <a href=\"mailto:korodi.rita@emk.semmelweis.hu\" target=\"_blank\" rel=\"noopener\">korodi.rita@emk.semmelweis.hu<\/a><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Training Objective To train a group of professionals with innovative skills who can participate in solving problems related to preserving and restoring human health, or preventing the deterioration of chronic conditions, using modern data science approaches. Our expert team aims to ensure that data-driven healthcare and artificial intelligence solutions evolve into system-level capabilities in Hungary. &hellip;<\/p>\n","protected":false},"author":102350,"featured_media":23064,"parent":14679,"menu_order":2,"comment_status":"closed","ping_status":"closed","template":"template-fullwidth.php","meta":{"_acf_changed":false,"footnotes":""},"categories":[],"tags":[],"class_list":["post-27966","page","type-page","status-publish","has-post-thumbnail","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/semmelweis.hu\/emk\/wp-json\/wp\/v2\/pages\/27966","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/semmelweis.hu\/emk\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/semmelweis.hu\/emk\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/semmelweis.hu\/emk\/wp-json\/wp\/v2\/users\/102350"}],"replies":[{"embeddable":true,"href":"https:\/\/semmelweis.hu\/emk\/wp-json\/wp\/v2\/comments?post=27966"}],"version-history":[{"count":1,"href":"https:\/\/semmelweis.hu\/emk\/wp-json\/wp\/v2\/pages\/27966\/revisions"}],"predecessor-version":[{"id":27967,"href":"https:\/\/semmelweis.hu\/emk\/wp-json\/wp\/v2\/pages\/27966\/revisions\/27967"}],"up":[{"embeddable":true,"href":"https:\/\/semmelweis.hu\/emk\/wp-json\/wp\/v2\/pages\/14679"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/semmelweis.hu\/emk\/wp-json\/wp\/v2\/media\/23064"}],"wp:attachment":[{"href":"https:\/\/semmelweis.hu\/emk\/wp-json\/wp\/v2\/media?parent=27966"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/semmelweis.hu\/emk\/wp-json\/wp\/v2\/categories?post=27966"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/semmelweis.hu\/emk\/wp-json\/wp\/v2\/tags?post=27966"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}