For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| DBA4033 | AI in Marketing | 3 | 6 | Major | Bachelor/Master | Business Administration | Korean | Yes | |
| Artificial Intelligence technologies revolutionalize the business world. AI Marketing (AIM in short) will significantly improve the productivity of manufacturng and distribution and will bring deep challenges to how marketing is done. Specific areas of study are as follows: 1. The present and future of AIM 2. Philosophical Backgrounds, and Ethical Considerations of AIM 3. Search and Logic in AIM 4. Planning and Problem Solving in AIM 5. Knowledge Representation and Experts in AIM 6. Quantifying Uncertainty in AIM 7. Probabilistic Reasoning in AIM 8. Natural Language Processing and Chatbots in AIM 9. Deep Learning and Classification in AIM 10. Neuroscience and Marketing Artificial Intelligence 10. Algorithms of AIM 11. Marketing Mix Model and System using AIM 12. Creative AIM using Generative Adversatial Networks with Python (Teaching Machines to Write, Paint, and Compose) | |||||||||
| DBA5114 | Special topics in Business Process Management and Machine learning | 3 | 6 | Major | Master/Doctor | 1-4 | Business Administration | English | Yes |
| Business process management, or BPM, aims to maintain corporate competitiveness by managing corporate management procedures so they may actively respond to changes in market conditions. Businesses need to adopt AI machine learning techniques in BPM to be competitive because the industry is changing swiftly and there is more rivalry than ever. Machine learning (ML) is responsible for a significant amount of the current achievements in artificial intelligence (AI). Machine learning can be broadly classified into two categories: single-label and ensemble approaches. Support Vector Machine (SVM), Neural Network (NN), Decision Tree (DT), Logistic Regression (LR), and Nave Bayesian Network (NBN) are among the single-label techniques. Ensemble techniques encompass a wide range of algorithms, such as Ada Boost (AB), Stacking (ST), Random Forest (RF), Bagging (BA), and Rotation of Forest (RoF). Furthermore, in the realm of natural language processing, deep learning techniques like Attention, Transformer, and BERT have gained popularity recently. CNN, LSTM, and RNN are a few examples of deep learning approaches that have grown in popularity. These advances in AI have demonstrated remarkable reasoning abilities. It currently demonstrates reasoning and problem-solving abilities that are superior to those of seasoned specialists with a high degree of experience and sophisticated BPM problem-solving capacity. It has proven to be successful and proficient in every area of modern BPM. | |||||||||
| DBA5115 | Special topics in AI Digital agent and management | 3 | 6 | Major | Master/Doctor | 1-4 | Business Administration | English | Yes |
| Following OpenAI's November 2022 launch of ChatGPT, business leaders have begun implementing "digital agents" or intelligent chatbots after realizing the profound impact these artificial intelligence (AI) tools have on organizational management. These chatbots are actively being used to improve the effectiveness of management. Using LLM (Large Language Model) technology, which leverages the capabilities of generative AI, or GAI, ChatGP is a digital agent. The aim of this course is to provide students with an understanding of the approaches and applications of artificially intelligent digital agents in order to handle decision-making difficulties in management and improve management efficacy in general. The aims and objectives of the course can be summed up as follows. With a focus on digital innovation, marketing, human resource management, finance, and accounting management, this course intends to give students a grasp of the training process for AI digital agents. The practical implementation of management practice procedures, or MLOPs (Machine Learning Operations), will be the main emphasis of the course. - The process of building chatbots using sLLM (small LLM) technology and pre-existing legacy databases will be taught to students. This strategy has become increasingly popular in multinational companies as a result of ChatGPT's outstanding accomplishments. - Students will also look at examples and noteworthy cases that show improved managerial efficacy. | |||||||||
| EPN2004 | Launching a Startup Venture | 3 | 6 | Major | Bachelor | 1-4 | Entrepreneurship & Innovation | Korean | Yes |
| This course provides tomorrow's entrepreneurs with the tools to launch a successful new business in a global marketplace, following the logical development process: from initial idea, to developing and testing a business model, to designing a business and preparing for growth. This class deals with the foundations of entrepreneurship and the main entrepreneurial activities such as developing and testing of a new business model through feasibility analysis. Students will also learn how to plan for nurturing an effective, scalable startup organization. | |||||||||
| EPN2006 | Entrepreneurial Competencies and Innovation | 3 | 6 | Major | Bachelor | 1-4 | Entrepreneurship & Innovation | Korean | Yes |
| This class allows students to explore entrepreneurial mindset and competencies where concepts are practiced and applied to actual context. This class defines entrepreneurial competencies as consisting of five components - "starting with why" "working with empathy" "getting validated and iterate" "enabling innovation" and "collaborating to grow." Workshops and dialogue sessions are main pedagogical tools and therefore students are expected to actively invovled in the learning process as self-directed learners. | |||||||||
| EPN2011 | Fundamentals of Team entrepreneurship | 3 | 6 | Major | Bachelor | Entrepreneurship & Innovation | Korean | Yes | |
| This class is offered for those who participate in team entrepreneurship programs developed according to MTA Change Maker Lab or Tiimiakatemia Methods (TM) in general. | |||||||||
| EPN2012 | Advances in Team entrepreneurship | 3 | 6 | Major | Bachelor | Entrepreneurship & Innovation | - | No | |
| This class is offered for those who participate in team entrepreneurship programs developed according to MTA Change Maker Lab or Tiimiakatemia Methods (TM) in general. Those who enroll in these programs for the 2nd time must register for this class. | |||||||||
| EPN3011 | Social Venture Capstone Design | 3 | 6 | Major | Bachelor | Entrepreneurship & Innovation | - | No | |
| In this class, students challenge the real problems faced by social ventures. For this, students learn how to collect analyze data from the field in order to identify the problems in an accurate and complete way. They have an opportunity to collaborate with the social ventures participating and have their ideas implemented. They also experience how social impact by their projects can be measured. | |||||||||
| EPN3012 | Entrepreneurship for Active Citizens | 3 | 6 | Major | Bachelor | Entrepreneurship & Innovation | Korean | Yes | |
| Through this course, students expect to understand not only themselves but also the people around them. Moreover, they would understand how their culture has been forming and changing. In the class, students would participate the dialogue and we expect the dialogue helps student to develop key leadership skills such as listening and sharing opinions. Also, the students will spend time looking at the assets and resources in their communities to get the insights which could bring a positive social change. Then, students would have a chance to develop and implement a social action project to make the positive change to the communities, using the skills which the students have learned through the course. | |||||||||
| ERC3001 | Global Capstone Design | 3 | 6 | Major | Bachelor | 3-4 | Engineering | Korean | Yes |
| This course covers the innovative design process based on international and interdisciplinary design teams by exploring users' various needs, defining design problems, reflecting practical constraints, generating diverse concepts, evaluating and refining final solutions and prototyping. The multidisciplinary design theories and methodologies will be addressed to guide the design process. Therefore, in this course, core capabilities for next generation engineers such as global competitiveness, innovation ability and interdisciplinary capstone design ability can be significantly fostered. | |||||||||
| 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. | |||||||||
| FIT4001 | FinTech Startups and Venture Financing | 3 | 6 | Major | Bachelor/Master | 3-4 | FinTech | - | No |
| This is a course in FinTech Startups and Venture Financing for FinTech master or undergraduate students in business major. Students can learn how to develop business models in fintech area and how to raise capital from venture capital to grow fintech start-ups. | |||||||||
| FIT4002 | FinTech and Financial Law Practice | 3 | 6 | Major | Bachelor/Master | 1-4 | FinTech | Korean | Yes |
| This course aims to help those students who seek to establish FinTech startup companies or engage in FinTech business, and the students are able to learn legal and regulatory issues and practices in the FinTech business and industry. | |||||||||
| FIT4003 | Financial Derivatives | 3 | 6 | Major | Bachelor/Master | 1-3 | FinTech | Korean | Yes |
| The objective of this course is to introduce key building blocks of financial derivatives to FinTech-oriented students. By combining analytical models with numerical examples, exercises, and case studies, the course emphasizes practical applications of financial engineering tools. Main topics cover various aspects of forward contracts, futures, options and swaps. The course will focus on hedging and pricing of financial derivatives. | |||||||||
| GBA2001 | Macroeconomics | 3 | 6 | Major | Bachelor | 2 | - | No | |
| Lectures emphasize the use of basic probability concepts and statistical theory in the estimation and testing of single parameter and multivariate relationships. In computer labs, using Microsoft Excel, each student calculates descriptive statistics, probabilities, and least squares regression coefficients in situations based on current business and economic events. | |||||||||