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Course&Curriculum

For more details on the courses, please refer to the Course Catalog

교육과정
Code Course Title Credit Learning Time Division Degree Grade Note Language Availability
DSC3009 Principles and Practice in Data Mining 3 6 Major Bachelor 3-4 Data Science English Yes
This course will provide the students with understanding of the fundamental data mining methodologies, and with the ability of formulating and solving problems with them. The particular attention will be paid to practical, efficient and statistically sound techniques. capable of providing not only the requested discoveries, but also the estimates of their utility. This class will be focused on hands-on experiences using data mining software. Students will have an opportunity to develop intuition needed to safely navigate through the complicated environment of today‘s data mining business market.
DSC3011 Applied Machine Learning 3 6 Major Bachelor 3-4 Data Science English Yes
The course introduces core machine learning tasks, algorithms, and techniques that are widely used in real-world machine learning projects. Major machine learning tasks such as classification, clustering, and regression will be introduced with widely used algorithms for the tasks. In addition to the tasks and algorithms, techniques such as data preprocessing, dimensionality reduction, model evaluation that are important for implementing machine learning applications will be covered. Students will learn machine learning by practicing with Python-based open source machine learning packages.
DSC3012 Principles and Practice in Social Data 3 6 Major Bachelor 3-4 Data Science - No
This course introduces the basic concepts of social media analysis methodology and covers practical skills needed in analyzing live social data. The main objective of this course is to provide students with solid grasp of social media data and ability to analyze them. During the practice session, students will learn how to develop ontology needed for effective and efficient processing of social data. Furthermore, this course introduces basic skills needed in using analysis software such as SAS Enterprise Content Categorizer. Students will also learn basic concepts of SAS ECC design and data management given topics to analyze. Based on analysis results of SAS ECC data, students will learn how to generate insight reports for general managers.
DSC3013 Introduction to Deep Learning 3 6 Major Bachelor 3-4 Data Science - No
This course aims to provide basic knowledge and practical skills in deep learning. It starts with an introduction to neural networks, which is the basic building block for deep learning. Students will be exposed to the issues associated with building and training a deep neural network taking into consideration other facets such as fully connected layers, convolutional layers and recurrent layers. Major deep learning architectures such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) will be discussed. Practical assignments in training deep neural networks using state-of-the-art frameworks (e.g. TensorFlow, PyTorch, Keras) will assist in grasping the technical skills required to be a deep learning data scientist. Students are assumed to have basic knowledge in programming (Python/R), linear algebra and calculus, and ideally machine learning.
DSC3021 Introduction to Artificial Intelligence 3 6 Major Bachelor Data Science English Yes
This course aims to teach the fundamentals of modern artificial intelligence, such as the concepts of intelligence and intelligent agents for starters. Next, it will probe into problem solving, introducing the notion of search. Then, the basics of knowledge representation and reasoning, such as logic and planning will be explored. Machine learning, a fast growing subfield of AI will also be covered. Further topics would include, but not limited to, foundations of natural language processing, semantic web, robotics and computer vision, concluding the communication, perceiving and acting of a rational agent. This is an introductory course and would be suitable for anyone interested to get started in AI. Students will be given assignments with minimal or no programming required.
DSC3024 Location-based Data Analytics 3 6 Major Bachelor Data Science - No
Students in this course will learn Geographic Information System(GIS) and its application. GIS is a tool for acquiring, storing, analyzing and processing of geographic data. Students will be exposed to a variety of GIS applications and methods to utilize location-based data.
DSC3032 Deep Learning 1: Foundations and Image Processing 3 6 Major Bachelor 3-4 Data Science English Yes
This course aims to provide practical skills in deep learning and in particular, image processing. Deep learning is at the core of the AI revolution and data science. It starts with an introduction to neural networks (NNs) and tensors, which are the basic building blocks for deep learning. Using Python-based libraries and PyTorch framework in the Google Colaboratory environment, students will dive in with coding simple NNs to deep NNs to classify fashion items, recognise handwritten digits, and even distinguish cats from dogs from images. Deep learning architectures such as multi-layer perceptrons, convolutional neural networks (CNNs), VAEs and GANs for image processing will be explored. Practical assignments in training deep learning models using classic datasets (MNIST, CIFAR-10, etc.) and well-known models (Inception v3, AlexNet, etc.) will assist in grasping the technical skills required. Students are expected to have basic knowledge in Python and basics in AI/machine learning.
DSC3033 Deep Learning 2: Natural Language Processing 3 6 Major Bachelor 3-4 Data Science English Yes
This course aims to provide practical skills in natural language processing (NLP). Natural language is used everywhere, not just in our everyday speech, but also in digital platforms in the form of textual data. NLP is a fast evolving field that is making waves today. Using the latest technologies, such as PyTorch and Hugging Face, students will first learn how textual data is preprocessed and prepared before being fed into deep learning models. Deep learning architectures for NLP such as recurrent neural networks (RNNs), Sequence2Sequence, and Transformers will be explored in detail. NLP tasks such as sentiment analysis, machine translation and text completion will be implemented in practical labs and assignments. Students should have good working knowledge in Python and some basics of deep learning (e.g. taken Deep Learning 1).
ERP4001 Creative Group Study 3 6 Major Bachelor/Master - No
This course cultivates and supports research partnerships between our undergraduates and faculty. It offers the chance to work on cutting edge research—whether you join established research projects or pursue your own ideas. Undergraduates participate in each phase of standard research activity: developing research plans, writing proposals, conducting research, analyzing data and presenting research results in oral and written form. Projects can last for an entire semester, and many continue for a year or more. SKKU students use their CGS(Creative Group Study) experiences to become familiar with the faculty, learn about potential majors, and investigate areas of interest. They gain practical skills and knowledge they eventually apply to careers after graduation or as graduate students.
ISS3090 Technology, Society and Sustainability 3 6 Major Bachelor 1-4 - No
We will learn about how the technology and society have been changed and effected to each other. In addition to that, we will discuss about how we develop and manage our technology and society to be sustainable.
ISS3183 Human Computer Interaction 3 6 Major Bachelor - No
This course covers the basic concepts, fundamental theories and current researches in humancomputer interaction. Topics include principles, theories, methodologies, design, implementation, evaluation and research in computer interfaces. The objectives of this course are:  to familiarize students with basic concepts of human computer interaction;  to introduce students to theories and principles in computer interface design;  to develop students’ ability to design, conduct and analyze user studies for computer software; and  to provide students with the knowledge of the design process for user interfaces.
ISS3198 Artificial Intelligence 3 6 Major Bachelor - No
This course aims to teach the fundamentals of artificial intelligence starting with the concepts of intelligence, rationality and intelligent agents. Next, it will probe into problem solving, introducing the notion of search by drawing examples from puzzles and games amongst others. Then, the basics of knowledge representation and reasoning, such as logic and planning will be explored. Machine learning, a fast growing subfield of A.I. will also be covered focusing on technologies and real-world applications such as games, biomedical applications, social networks and smart technologies. Further topics (time-permitting) include the impact of major A.I. areas such as robotics and computer vision, natural language and speech processing in our society today. This is an introductory course and would be suitable for anyone interested to delve deeper into A.I. in the near future. Students will be given assignments that do not require any programming.
ISS3217 Business Analytics 3 6 Major Bachelor 1-4 - No
This course will provide students with an introduction to business analytics. This course will change the way you think about data and its role in business. We will examine how data analysis technologies can be used to improve decision-making. We will study the fundamental principles and techniques of business analytics, and will examine real-world examples and cases to place datamining techniques in context and to develop business analytic thinking.
ISS3219 Digital Marketing 3 6 Major Bachelor - No
The goal of this course is to provide insights on how modern industry is adopting new emerging media and technologies as marketing tools. In a digital sphere, modern consumers go through the stages of awareness, intent, conversion and finally retention. The course will focus on how digital media have revolutionized the interactions between firms and consumers along this journey. New technologies offer powerful tools to reach consumers along the funnel: online display ads raise awareness, search listings reach consumers with intent, e-commerce facilitate conversion, and social medial both energizes and retains customers.
ISS3220 Consumer Behavior 3 6 Major Bachelor - No
The goal of this course is to provide 1) an understanding of the dynamics that underlie consumer behavior (CB) and the factors that influence these dynamics, and 2) experience in extending beyond knowing and understanding to applying said knowledge. For many aspects of the course experience, the guiding question will be: “How could you apply the concepts and principles form assigned reading to develop, improve, package or promote your product/service/issue in a way likely to impact positively upon consumers’ mental states and/or behavior? ”