Program Overview
Yamanashi Gakuin University's Interdisciplinary Data Science major equips students with technical data science skills and a deep understanding of other disciplines like Psychology, Political Economy, or Finance. This interdisciplinary approach enables graduates to solve real-world problems with a holistic perspective, preparing them for careers in data analysis, research, policy analysis, and more.
Program Outline
Degree Overview:
Overview:
The Interdisciplinary Data Science major at Yamanashi Gakuin University's International College of Liberal Arts (iCLA) is designed to equip students with the skills essential in the 21st century. This program combines technical skills in data science with a deep understanding of other disciplines like Psychology, Political Economy, or Finance. This approach allows students to solve real-world problems with an interdisciplinary lens that considers multiple perspectives.
Objectives:
- Nurture critical thinking and problem-solving capabilities by transcending technicalities.
- Foster an appreciation for the intersection of data science with other disciplines.
- Prepare students for careers where navigating data in diverse contexts is crucial.
Program Description:
The Interdisciplinary Data Science major is carefully crafted to meet the growing demand for professionals well-versed in data analytics, while emphasizing ethical considerations in data utilization.
Outline:
Program Content:
The program includes coursework in Programming, Mathematics, Statistics, and area studies, focusing on either Finance, Political Economy, or Psychology.
Program Structure:
The curriculum is structured into three main levels:
- Introductory Courses
- Core Courses
- Advanced Courses
Course Schedule:
- Introductory Courses:
- Academic Reading Across Disciplines
- Composition 1
- Composition 2
- Expository Research Writing
- Foundation for College Success
- Modern World History
- Japanese Language 1
- Japanese Language 2
- Core Courses:
- Coding Bootcamp: Python
- College Algebra
- Data Visualization Techniques in Python
- Introduction to Computer Science
- Introduction to Data Science
- Introduction to Python Programming
- Machine Learning
- Mathematics for Data Science
- Science, Society & Self
- Statistics
- The Art & Science of Decision-Making in an Era of Accelerating Change
- Finance Pathway Courses:
- Accounting
- Econometrics
- Financial Management
- Investment
- Introduction to Fintech: Reshaping the Financial World
- Portfolio Management
- Risk Management
- Political Economy Pathway Courses:
- Introduction to Political Science
- Microeconomics
- Political Economy of Development
- Political Economy of Trade and Industrial Policy
- Psychology Pathway Courses:
- Introduction to Psychology
- Social Psychology
- Economic Psychology
- Cyberpsychology
- Consumer Psychology
- Research Design
- Advanced Courses:
Teaching:
Teaching Methods:
The curriculum is structured into theoretical lessons, practical sessions, and research-based projects.
Faculty:
The program faculty includes renowned scholars and researchers from diverse disciplines like Computer Science, AI, Political Economy, Experimental Neuropsychology, and Developmental Psychology.
Unique Approaches:
- The program emphasizes interdisciplinary learning to provide a holistic education.
- Students work on real-world applications, gaining practical insights.
- The program features a collaborative learning environment that encourages teamwork.
Careers:
Potential Career Paths:
Graduates with Interdisciplinary Data Science can pursue careers in the following sectors:
- Data analyst, applying skills to solve problems in financial, political, or psychological contexts
- Pursuing postgraduate studies in Data Science, Finance, Political Economy, Psychology, or related fields
- Research projects at the intersection of Data Science with other disciplines
- Policy analysis using data-driven insights in the political landscape
- Consultancy services, offering data-driven solutions to businesses or organizations
- Non-profit and social impact organizations, leveraging data for positive change
- Education, teaching Data Science or related subjects
- Start ventures focused on data-driven solutions for financial, political, or psychological challenges
- Data journalism, explaining complex issues through data visualizations