Course Outline

Common RISE

In order to strengthen the capacity of research for students and faculty
Common INTERNSHIP(Ⅲ-1)

This program is designed to give students experience in their chosen career field and are an extension and application of prerequisite academic skills.
Common RISE

In order to strengthen the capacity of research for students and faculty
1 DISCRETE MATHEMATICS

Fundamentals of set theory, graph theory and algebraic structures with applications in computing
1 Introduction to Computer Engineering

This course provides fundamental concepts in computer science such as architecture, data structure, programs, etc, for better understanding of computer engineering. Simple programming labs can be provided.
1 Introduction to Programming

Learning the fundamentals of computer programming by Python programming language. This is focused for freshmen who begin to learn programming languages.
1 CALCULUS(1)

As a basic mathematics course for students in natural science college we study differentiation and integration of one variable real-valued functions, emphasizing basic concepts and applications. The topics are limit functions, continuity, derivatives, polar coordination and proper integrals.
1 Introduction to Data Science

This course aims to learn python and several important libraries for data analysis including numpy, pandas and mathplotlib which are useful for acquisition, trimming, and handling of data. Students are required to enhance their understanding of data science and to improve python skills.
1 PROBABILITY AND STATISTICS

It organizes basic framework of data structure, probability and statistics and learns method to apply to computer programming.
1 C language

The C language has been the foundation of many high-level programming languages and used for making most modern operating systems, including Unix and Linux. Therefore, learning the C language can be a good starting point for becoming a good programmer, and also can help students understand computer science. To learn C language, students will theoretically learn the basics of programming in C, the syntax of C, and how to solve a given problem in C language.
1 CALCULUS(2)

As a contiunation of "Caculus (1)" we study properties of partial derivatives, multiple integrals, series and matrices.
2 Java Language

To develop basic Java programming skills, students learn basic grammar, standard class library, exception handling, I/O, graphics of Java. Also the class provides overview of object-oriented programming.
2 DATA STRUCTURE

Deals with basic data structures including stack, queue, list, tree, graphs used for computer programming.
2 Data Programming

In this course, students will learn methods for analyzing and studying data, covering a comprehensive process that includes data cleaning, transformation, pattern analysis, visualization, and the development of predictive models. Programming exercises are conducted in parallel to develop foundational skills for analyzing real-world data.
2 DIGITAL ENGINEERING

This course introduces students to the architecture and design of digital systems. The main topics covered are : boolean algebra and logic gates, combination logic design, sequential logic design, registers and counters
2 LINEAR ALGEBRA

This subject covers how to analyze the structure of linear system in vector, matrix, and vector space. This course covers the concept of linear algebra and its fundamental theory.
2 Basic simulation lab with Matlab

This class learns simulation methods and tools for various engineering problems using Matlab, which is widely used for solving various engineering problems.
2 C++ Language

This course aims to introduce basic and overall concepts of C++ programming. Students will learn how to declare and use classes and also advanced skills such as inheritance and polymorphism using practical applications.
2 COMPUTER ARCHITECTURE

This class is to understand the general hardware and software architectures by studying logic circuits, central processing units, storage devices, control devices and peripheral devices, and designing a basic computer.
2 Linux System

The operating system used by AlphaGo is Ubuntu Linux. In this course, students will learn how to use real Linux systems, which are widely used as open source operating systems for developing AI technology, from programming to programming. The goal of this course is to develop the foundational skills to effectively use and apply real world Linux systems that are expanding their applications. This course covers basic Linux usage, Linux system administration, Linux server construction, Linux shell programming, and Linux system programming, etc.
2 Mobile Software

This course gives a chance of full understanding of wireless internet application programming dedicated to mobile handheld terminals and/or PDAs.
2 NUMERICAL ANALYSIS

Numerical analysis is a subject which finds solutions of mathematical problems numerically. This course covers the solution of equations, interpolation, linear algebra, ordinary differential equation by numerical method, and applications which accompany them.
2 System Programming

System software is computer software designed to operate the computer hardware by direct control, integration, and management of hardware components, including operating systems, device drivers, programming tools, compilers, assemblers, linkers, loaders, utilities, and etc. This class aims to make students understand how computers systems and software programs actually work by learning functions of system software and its programming methods. To this end, this class deals with machine language, assembly language, memory access control, flow control, debugging methods, etc.
2 Windows Programming

To understand how Windows OS and Windows applications work, students learn how to program applications using Windows SDK. Programming languages used are C and C++. To develop Windows applications, MFC and Windows standard developments tools are used.
3 Database

It learns database's basic concept and relational Database's language(SQL and so on), and deals with model for database design and object oriented database.
3 OPERATING SYSTEM

This course introduces the fundamentals of operating system processes, synchronization, storage operation, resource distribution, system security, etc., and develops case studies of large computers and actual design composition skills.
3 Machine Learning

This course introduces fundamentals of machine learning. It consists of supervised/unsupervised learning, Bayesian decision theory, parametric/non-parametric methods, decision trees, estimation theory, linear discrimination, multi-layer perception, clustering, reinforcement learning and other issues. The class also talks about the deep neural network as a state-of-the-art technology of machine learning theory.
3 Data Mining

As various forms of business activities take place in the digital age, it has been recognized as important to effectively manage and utilize various types and large volumes of data. In addition to effectively managing and utilizing this large amount of data, it has become important to extract meaningful information from these data and utilize my business intelligence. The activity of finding hidden knowledge or patterns in large volumes of data and gaining insight into the data is called business data mining, and many companies are improving their competitiveness through business data mining. Therefore, this course covers the basic analysis techniques of data mining and teaches how to apply them to business data.
3 DATA COMMUNICATION

This course introduces students to the digital transmission of communication systems. The main topics covered are : signal concept, modulation/demodulation, multiplexing, error recovery and medium access control
3 SOFTWARE ENGINEERING

Understands methodologies and tools throughout the software lifecycle of development and maintenance, and learns knowledge for software management to produce good quality software at low cost and effort.
3 WEB PROGRAMMING

This course gives an ability of implementation of web server programming based on either ASP(or latest version) or LAMP(Linux, Apache, MySQL and PHP or latest version). Particularly, web application based on CBD lay great emphasis on this course..
3 Advanced Programming Language

We will learn about syntax, semantics, and type system, which are the main topics of programming language. Also, the principle of control structure, the principle of function operation, object-oriented language, and functional language will be covered in some detail. We aim to improve the ability to use the principles and implementations of programming languages in various related fields.
3 Algorithm

Understands theoretical backgrounds of algorithms used for sorting, searching, string processing, geometry, dynamic programming and learns about performance analysis methods of algorithms.
3 Capstone Design (1)

The goal of this course is to design new algorithms, programs, and/or systems that can solve practical problems. To this end, students leverage a variety of knowledge and technologies that are learned from courses and from out of classes. Students may bring their graduation projects to the classroom where they design fundamentals of their project solutions and develop prototype systems.
3 COMPUTER NETWORK

This course covers the network architecture and protocol of computing nodes. The main topics covered are : computer networks and Internet, application layer, transport layer(TCP, UDP) and network(IP) layer.
3 Server construction

Server construction and management refers to safely and systematically operating and managing server systems installed in corporations or institutions and providing various services to users. To this end, server management requires a general understanding of the basic structure of hardware, OS, network, and DB. In this course, we learn server management techniques in the rapidly growing cloud environment. In particular, from a practical point of view, it builds the latest server infrastructure for practice, such as Linux and Kubernetes, which are most commonly used, and introduces server management techniques.
3 System security and Hacking

In this course, we learn basic knowledge necessary for computer system hacking, including the memory operating principles of 80x86 systems and assembly language grammar. Based on system theory, we understand and practice computer system hacking technologies such as password cracking, reverse engineering, buffer overflow, format string, and backdoor. In addition, we learn various defense methods to prevent those attack cases, which are system log analysis and intrusion tracking methods.
3 Natural Language Processing

Natural language processing (NLP) is one of the main research areas of artificial intelligence that enables machines to understand human language. In this course, we will learn about rule-based and statistical methods, which are traditional processing methods of NLP, and machine learning and deep learning techniques, which are being mainly studied recently. Also, how each method is applied in major application fields of NLP, such as sentiment analysis, machine translation, and Q&A. This course aims to acquire linguistic knowledge related to NLP and to understand how natural language processing technology works.
3 Intelligent Information Systems

Intelligent information system is a computerized system for creation of information from data. Intelligent information System course teaches the theory and practice for systems required for the process of producing information through data gathering, data storing, data structuring, information extraction, information retrieval, and information distribution. This course provides the basic notions of real-world applications, for example, text/language processing, information retrieval/extraction, recommendation systems, social network analysis, etc., based on the understandings on information theory. Moreover, this course includes practice to learn and experience efficient processing algorithms as well as effective representation models.
3 Computer Graphics

This is a basic lecture on computer graphics, and learns basic theories and algorithms of various computer graphics such as components of computer graphics, coordinate system, OpenGL pipeline, model transformation, viewpoint transformation, projection, and rasterization using OpenGL.
4 Capstone Design (2)

The goal of this course is to advance algorithms, programs, and/or systems that can solve practical problems. To this end, students leverage a variety of knowledge and technologies that are learned from courses or from out of classes. The course runs laborabory, and students are recommended to bring their graduation projects. Students implement and evaluate their algorithms, programs, and/or systems in the course.
4 GAME PROGRAMMING

This course aims to introduce basic theories and techniques of game programming. It concentrates on the programming aspects for developing interactive three dimensional games. Particular topics include real-time rendering and game interface.
4 Artificial Intelligence and Deep Learning

Deep learning, a core technology of artificial intelligence, has come to be a technology that anyone can use in everyday life like electricity. This course is an undergraduate course that will provide a foundation for deep learning. Understand the basic concepts of deep learning and learn various models of deep learning through hands-on experience. In the first half, students understand the operation principle of the artificial neural network which is the fundamentals of deep learning. In addition, students will learn the basic concepts of various models of deep learning by implementing artificial neural network step by step with Python codes. In the second half, we will learn basic usage of TensorFlow and then implement the basic concept of deep learning and various deep learning models learned in the first half. Students also learn to design and implement their own deep learning projects that use real world data to solve their own problems.
4 COMPILER DESIGN

You will learn about the front-end part of a process of compiler design including lexical analysis, syntax analysis and semantic analysis. You can also learn how to use well-known compiler generation tools such as Lex(flex) and Yacc(bison). To increase the ability of practical application, several topics including HTML parsing, a transformation of web document are covered.
4 Cloud Computing

Starting with an overview of modern distributed models, this lecture deals with the design principles, system architectures and innovative applications of parallel, distributed and cloud computing systems. This lecture intends to integrate parallel processing technologies with network-based distributed systems, emphasizing scalable physical systems and virtualized data centers and cloud systems with its enabling technologies, including clustering and virtualization.
4 Intorduction to Bigdata

Big data is a data sets that are too large or complex, and often not structured to be analyzed by traditional data processing techniques. Its amount is exponentially increasing owing to recent development of IT including storage techniques, and, accordingly, big data analysis techniques are getting more important for various fields such as marketing, researching and so on. The goals of this course are to understand various kinds of big data and analysis techniques including frequent pattern analysis, text analysis and graph analysis, and to learn how to find meaningful and valuable information applying those techniques to real-world big data.
4 Entertainment Software

The entertainment software course provides practical knowledge and practices regarding structures and components of entertainment softwares. During the course, students will study entertainment aspects of application softwares as well as game softwares and also learn how to design and develop creative games.
4 Introduction to Speech Recognition

This course covers the entire procedure of automatic speech recognition which is a core technology of HCI (Human Computer Interface). This course begins with an overview of the state-of-the-art speech recognition technology and its applications, and then deals with human speech production and perception procedures. It is followed with the detailed lecture on the core procedures of speech recognition including acoustic modeling and decoding using HMM (Hidden Markov Model). Students will obtain an ability to conduct simulation of speech recognition using the open software toolkits.
4 Topics on Information Security

As the social dependency on IT(information technologies) for processing important information of individuals and nations, security becomes a more critical issue. It is essential to obtrain systematic security measures to treat information in a safe manner in the current Internet environment. In this lecture, students are instructed to study encryption algorithms as basic methods for the security and various mechanisms to construct secure computer and network systems. Also, they learn authentication, digital signature, e-mail security, communication security, and other network security issues including web security. Security menagement issues such as security policy, risk analysis, and audit are also handled. All these recent security techniques attained through this study are applicable to real fields such as computation, information processing, and mobile systems.
4 COMPUTER VISION

Learns the algorithm for basic image recognition and processing in theory, and performs projects to develop basic computer vision software by applying theories.