Standard Course

Overview of Data Science

Overview of Data Science was introduced as an elective course in the core curriculum in the 2020 academic year. The course’s objective is to help students understand how data is used in contemporary society and daily life, the methods for utilizing it, and the challenges associated with its application. Starting in the 2022 academic year, it became a university-wide compulsory course, which students typically take during their first year. It serves as an introductory course to the data science curriculum. Based on the knowledge acquired in this course, students will deepen their studies through consecutive courses.

Feature 1: Overview rather than Introduction

Instead of providing a basic introduction, this course offers a comprehensive overview of data science. Students will learn how AI and data science are used in various situations, including daily life, business, and public policy-making. They will learn through video lectures developed in collaboration with external organizations that utilize AI and data science in their business operations.

Feature 2: No prior knowledge of high school math required.

Students will learn various methods in statistics, data mining, and machine learning. Instead of emphasizing the mathematical underpinnings of these methods, the course will focus on helping students understand when and how they are applied, as well as how the analysis results are utilized. Hence, no knowledge of high school mathematics is required for this course. The content is accessible for beginners with a limited background.

Feature 3: No distinction among disciplines.

Students will refine their comprehension of foundational data science topics, such as its law and ethics, regardless of their academic discipline. Students will learn about international trends in data science, including the Personal Information Protection Law, OECD guidelines, EU data protection directives, consumer privacy rights charters, and the GDPR. They will also learn about the negative aspects, such as information leaks and data or algorithm bias.

Feature 4: Visualization of Learning Outcomes through a Learning Management System (LSM)

The course utilizes an LMS for several purposes, such as, but not limited to, viewing video materials, accessing lecture materials, submitting comments and questions about classes, and submitting assignments. The LMS stores all this data, enabling students to access their learning outcomes at any time.

Fundamentals of Data Science and Engineering

This course introduces the principles of data engineering with an emphasis on utilizing diverse data sources. Students will learn how to analyze and visualize data, as well as how to apply big data and AI programming.

Fundamentals of Artificial Intelligence

This course covers a variety of AI technologies and applications, as well as the fundamentals of machine learning. It encompasses a wide array of subjects, including the history of AI, societal concerns, emerging advancements, and the fundamentals of deep learning. It is arranged in an accessible way to all students, including those with limited backgrounds.

Programming for Data Science & AI

Programming in Data Science and Artificial Intelligence

This course is designed to apply the fundamental knowledge acquired up to this point to process and analyze real data by using tools and programming. Students will use Python exercises to apply their learning to their own fields of expertise.

Advanced Course

Examples: Advanced Course Pre-Approved Courses