Graduate Degree Program of Applied Data Sciences

Learn Data Science to Advance Your Learning in Your Career

Sophia University will launch the Graduate Degree Program of Applied Data Sciences (Master’s Program), a graduate school for the practical study of data science, in April 2023. The education of data science has been conducted mainly in the field of science and engineering at universities. However, in our rapidly changing society now needs to prepare itself for Society 5.0, a super-smart society. We not only require human resources with expertise in science and engineering, but also business people who have knowledge on data science and can read and understand data, solve problems, and apply and develop new business.

The Graduate Degree Program of Applied Data Sciences aims to nurture practitioners who possess both academic expertise and the practical skill to apply and deploy it in the modern society with “bridging theory and practice” as a key phrase. The three Graduate Schools of Economics, Science and Technology and Environmental Studies at Sophia University are collaborating to develop human resources who can respond to rapid changes in society and solve problems using their data science knowledge. Under the theme of applied data science, the three Graduate Schools have established an organized and systemized cross-divisional degree program. The program is designed to train professionals who will contribute to solving problems in the coming data-driven society and pioneer a new world.


Academic faculty members in this program will provide guidance mainly from an academic perspective, while practical faculty members will provide guidance with an emphasis on practical skills for students to become active in the modern society after completing the Master’s Program. Students will acquire the necessary knowledge to become practitioners who can lead our data-driven society immediately through practical training courses centered on exercises, elective courses that broadly cover the basic and applications of data science, and collaborative courses that broaden and deepen their academic knowledge in data science and business administration. In addition to the faculty members, we also offer a number of courses taught by lecturers dispatched from companies. In the second year, internships courses are offered in actual work sites to deepen the students’ understanding.

Granted Degree


Program Features

Learn from a Diverse Group of Faculty Members with Different Areas of Expertise and Practitioners at the Forefront of Business

The biggest feature of this program is its collaboration among faculty members from the three graduate schools that apply and develop data science (Graduate School of Economics, Science and Technology, and Global Environment Studies) and practitioners with extensive experience in data science especially in the field of business.

The collaboration of these graduate schools that are primarily based on economics, science and technology, and environmental studies enables students to cover diverse academic fields such as economics, business administration, science, engineering, informatics, and environmental studies. The curriculum and faculty organization are designed with a focus on fostering the ability to apply and develop these academic fields in the practical world.

Flexible Learning for a Diverse Group of Students with a Curriculum Optimized for Each Individual

This program accepts students from diverse backgrounds and fosters practitioners who will lead our data-driven society through their graduate studies. We do not set any requirements for entrance examination or admission, such as designating the field of study or undergraduate courses taken in the past, or work experience. Depending on the individual’s educational and professional background, students can brush up their existing knowledge or skills and build their own curriculum based on their ideal career.

Urban Campus with Classes Mainly Held in the Evenings on Weekdays for Working Students to Learn Easily

Part of its mission is to provide recurrent education for working adults, so the program offers daytime and evening classes. Classes are held mainly in the evening on weekdays, providing an environment that is conductive to learning for working people. The campus is located in front of Yotsuya Station, which is accessible by both JR and Tokyo Metro lines allowing students to easily commute to the school on their way home from work.

*Students are required to take certain number of courses offered during the daytime to complete the program.

Educational Policies




  1. 応用データサイエンスおよび関連分野において最先端で活躍できる専門知識を身につけるとともに、新手法の開発や新分野の開拓をできる力
  2. 自らの専門分野に加え、それ以外の自然科学あるいは社会科学との学際分野も含めて広範に学ぶことにより、データサイエンスが人間社会や地球環境に与える影響などを多面的に捉える力
  3. 専門分野に関する課題について、データの収集,分析,活用まで幅広く実行できる力
  4. 自らの研究成果を論理的に整理して的確に伝え、特定課題研究としてまとめる力
  5. 研究課題の達成を通じて、実社会においてグローバルレベルで即戦力となり、データ活用社会を牽引する力



  1. データサイエンスの基礎から実践まで幅広い分野を俯瞰し、本プログラムで学ぶ内容の理解を促すための必修科目として「データサイエンス概論」を1年次春学期に配置する。
  2. データサイエンスの基礎スキルやリテラシーの習得とあわせ、データを扱う上で配慮すべき倫理的側面の理解を促す講義・演習科目を1年次に配置する。
  3. データサイエンスおよび関連分野に関する学術的な視点や専門知識および実務で応用するための視点やスキルを習得する講義科目を1年次に配置するとともに、それらの視点や知識・スキルを実社会で活用する力を養う必修科目として「導入演習」を1年次秋学期に配置する。
  4. データサイエンスを応用した実例を体感し、データの収集,分析,活用等の実践力を習得するための実践系講義科目およびインターンシップ、学術的な応用力を養成するための様々な学問分野における分析手法や応用事例を学ぶ連携科目を2年次に配置する。
  5. 特定課題作成と口頭報告の能力を習得するための必修科目として、学術的なアプローチによる指導を行う「演習A」、それと並行して実社会での動向や事例を踏まえた指導を行う「演習B」を2年次に配置するとともに、両科目を横断する形での合同研究報告会を実施する。
  6. 研究を現実の社会問題に応用する力を習得するため、各専門科目においてディスカッションや演習を取り入れるとともに、関連学会への参加を促進する。



  1. データサイエンスに係る専門知識を積極的に活用し、現代社会における多様な課題の解決に取り組み、応用データサイエンスによって人間社会の発展に貢献できる学生
  2. 応用データサイエンスの知識・技術を用い、実践的データを活用した新たな分野を社会で開拓・発展させようという意欲をもっている学生

Faculty Members

Sumiko ANNO Professor

Research Areas Environmental health,Spatial Information Science: Applied research on environment and health environment using machine learning
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Tomi OHTSUKI Professor

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Yoshiko OHARA Professor

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Tetsuya HORIE Professor

Ikuko YAIRI Professor

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Masamitsu KURATA Associate Professor

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Hirotaka KOBAYASHI Associate Professor

Kasumi BAN Associate Professor

Yusuke FUKAZAWA Associate Professor

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Takao YAMANAKA Associate Professor

Haruka YAMASHITA Associate Professor

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