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What’s New Department of Data Science Latest News
Message from the Dean
FeatureFeatures
We define data science as "a science with an interdisciplinary framework for creating and implementing new value through problem-solving based on the analysis of various types of data." In other words, we believe that the role of data science is to generate new value by collecting and analyzing data to address the challenges and problems facing companies and society. To achieve this, students must not only study the three fields of "IT skills," "data analysis skills," and "management skills," but also acquire the organic combination of these skills: "IT skills x data analysis skills x management skills." Furthermore, learning data science and acquiring quantitative and logical thinking will also lead to improved communication and presentation skills.
Our department aims to train data science professionals by offering a practical and distinctive curriculum that fosters "IT skills x data analysis skills x management skills."
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Information technology-based learning
The ability to use information devices, computers, and software is required to collect, store, analyze, and visualize data. In addition, the ability to develop systems and software is required to create and implement new value. As part of the knowledge required for developing systems and software, students will learn about IoT, AI (artificial intelligence), databases, networks, security, programming, software engineering, systems engineering, and more.
In particular, in programming, students learn the basics using not only Python and R, which are often used in AI and data science, but also C and Java, which are used in software development, and also study data structures and algorithms to create efficient programs. Learning based on information technology is the greatest feature of the Department of Data Science, which is established within the Faculty of Information Science.
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Learning and entrance exams aimed at integrating the humanities and sciences
AI and data science have the potential to contribute widely not only to the planning and development of industrial products and goods, but also to corporate strategies and various operations, finance, economy, health, sports, and even government and local government policies and systems. Creating new value requires not only technology, but also interest and knowledge about systems such as people and society. For this reason, specialized subjects include business strategy, manufacturing, marketing, logistics, finance, education, and idea generation.
In addition, the Department of Data Science has both a public recommendation entrance exam and a general entrance exam, each with a "science" and "arts and science" format. We have adopted an entrance exam system that allows applicants to choose from a variety of subject combinations and evaluate the diverse academic abilities of applicants. We welcome the challenge of anyone interested in data science, regardless of whether they are in the arts or sciences.
*The content will vary depending on the entrance examination you are applying for. Please be sure to check the latest entrance examination guide for details of the entrance examination system.
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A wide range of general education options to choose from based on career path and interests
The common subjects of the Faculty of Information Science and Technology are composed of "Integrated Human Studies" and "Integrated Science". "Integrated Human Studies" is further divided into "Humanities and Social Sciences", "Foreign Languages", and "Health and Sports Sciences". The graduation requirement for the common subjects of the Department of Data Science is 36 credits or more, including 12 credits or more in "Humanities and Social Sciences", 8 credits in "Foreign Languages", and 2 credits in "Health and Sports Sciences".
The Department of Data Science aims to integrate the humanities and sciences, and is designed to allow students to fully study the humanities and social sciences in accordance with their individual career paths and interests. Of course, those interested in general science can also mix and match physics, chemistry, earth science, and biology subjects.
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Learning that focuses on practice, not just theory
Rather than just understanding statistical methods and theories, you will use computers and software to analyze real data and interpret the results. Learning that focuses on practice will foster a mindset of value creation. Use your laptop as your companion and enjoy a variety of data analyses.
Since 2019, the Faculty of Information Science and Technology has been running the "Hirakata Ideathon Hackathon Project," a joint industry-government-academia collaboration to solve local issues, in collaboration with Hirakata City Hall and the North Osaka Chamber of Commerce and Industry. In 2022, the project was renamed the "Social Open Innovation Challenge," and continues to receive support from many companies and organizations. It is an open event that students from other schools can also participate in. Form a team and take on challenges faced by companies and local communities.
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For high school students and working adults
Providing AI and data science education programsThe educational activities of the Department of Data Science faculty are not limited to university students. For high school students, we offer an "AI/DS course" consisting of one class on the overview of AI/DS, two classes on text mining, and four classes on programming using Python. For working adults, we offer a DX Innovation Leader Education Program (certificate program) for smart manufacturing, consisting of seven subjects: Data Science, Data Mining, Machine Learning Applications, IoT Design, Digital Twin Practice, Data Science Practice for Manufacturing, and Data Science Practice for Marketing.
We can flexibly provide educational programs that meet various needs. And by offering a variety of programs, education can be improved. This is one of the strengths of the teaching staff in the Department of Data Science.
ContentsList of each department's contents
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curriculum
Please click here for more information on the four years of study, lecture content, and global human resources.
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Laboratories and Faculty
In a variety of laboratories and under the guidance of highly-skilled faculty, you can learn everything from the basics of apps and programming to advanced information processing technologies.
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Employment and Career Paths
Find out more about the paths and employment opportunities available to you after graduation. Check out the diverse career possibilities available to you.
Learn through the video
Department of Data Science
Three Policies
FacilityFacility Introduction
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A vast campus towering over Hirakata.
The vast campus, located in northeastern Osaka, is equipped with a wide range of facilities related to information science.
Surrounded by a quiet residential area, you can study and participate in extracurricular activities in a peaceful environment.
Q&AFrequently asked questions
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What kind of department is the Department of Data Science? What are its characteristics compared to other departments?
The Department of Data Science aims to create new value to solve social and corporate problems through statistical analysis and information technology.
While the other four departments aim to create information technology, our department focuses on utilizing information technology and applying it to real-world issues. For this reason, the educational curriculum does not include the computer basics courses offered in the four existing departments (digital circuits, computer architecture, operating systems, etc.), but focuses on courses necessary for the use and development of information systems (programming, software engineering, database systems, information and communication networks, basics of information security, IT theory, etc.), and instead enriches courses related to "AI (artificial intelligence)," "statistical analysis," and "problem solving." -
I am a liberal arts student and I am interested in data science. Will I be able to study specialized subjects?
The curriculum of our department aims to equip students with the ability to create new value. To that end, we aim to equip them with statistics and information technology. However, the mathematics education that is the basis of data analysis and system optimization is a concern. For example, in two mathematics courses offered in the first semester of the first year (Linear Mathematics I and Calculus I), students are taught in small groups in two classes, and they steadily deepen their understanding using assignments.
In addition, specialized subjects include not only statistics and information technology, but also subjects related to social systems, corporate systems, and problem solving. Because it is a field that aims to integrate the humanities and sciences, the graduation requirements are designed so that students can freely choose humanities (linguistics, sociology, psychology, economics, etc.) and science (physics, chemistry, earth science, biology, etc.) subjects in general education according to their interests and career paths. Interest in data science and information technology and a good attitude towards classes are more important than high school courses (humanities, science, etc.). -
Are there any practical exercises or training in the first year?
In order to learn data science practically, various courses are equipped with exercises using real data and computers. It is important to firmly establish the foundations of learning in the first year. However, having opportunities to try out what you have learned and to be given hints on the goal of your studies certainly motivates you to learn.
Therefore, the Department of Data Science is planning a "Data Analysis Practice Seminar" for first-year students in December. This seminar will be in the PBL format, so students will form teams and present their own solutions to problems that do not have a definite answer. This time, the theme will be the declining population, an issue in Japanese society. First, students will receive training on analytical methods, then they will analyze and interpret publicly available social statistics data from prefectures in groups, and compete for their results in a presentation. This seminar is open only to those who wish to participate, but we are confident that it will stimulate participants' desire to learn.
ContactInquiries and Access
Faculty of Information Science and Technology Office Hirakata Campus Building 1, 1st floor
Reception hours: Weekdays 9:00-17:00
Please note that it may take some time to respond to inquiries during the summer and winter holidays.
