Automotive Software Major

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MSC (10 courses)

Calculus, Statistics for Big Data Analytics, Automotive Physics I, II, Computer Programming, Designing Computer 3D I, II, Basic Software Engineering, Linear Algebra, Automotive Mathematics

Course Description Prerequisite
Calculus This course is one of the most basic subjects for developing mathematical ability for engineers. In order to cultivate logical thoughts and qualities and to cultivate creativity, we focus on the foundations by understanding and acquiring the most basic concepts of mathematics.
Statistics for Big Data Analytics It aims to cultivate the ability to utilize the concepts and techniques in various application fields by teaching basic concepts of probabilities necessary for automotive engineering classes and statistical reasoning methods necessary for big data analysis. Calculus, Linear Algebra
Automotive Physics I The course focuses on the fundamentals of physics for the automotive engineering. Especially, the goal is understanding of natural phenomena and laws and understanding of mathematical interpretation as the basic process of physics that is the basis of automobile engineering. To educate students how to visualize physical phenomena, we use simulation software such as Mathematica or Matlab to simulate the theory.
Automotive Physics II
Computer Programming Through the C language, we learn basic grammar of computer programming and basic knowledge of computer structure, and learn how to solve a given problem using a programming language. In this course, the essential program theory and practical program methods of C language are practiced and practiced concurrently. Students will learn how to understand the logic of the program by using flow chart based visual programming tools, and learn basic knowledge of C language programming and practice to develop basic knowledge as a programmer.
Designing Computer 3D I This course is a basic course in design. We will use SW to model the 3D shape and practice SW. We plan to design product using direct CAD and output it to 3D printer for excellent design works and use it as teaching materials.
Designing Computer 3D II
Basic Software Engineering This course covers how to implement a full-fledged programming language such as C, Python, and other visual-based languages to implement computer software. Computer Programming
Linear Algebra The course aims to understand the fundamental concepts of matrices and vectors essential to the fourth industrial revolution course such as artificial intelligence and big data. Students will learn the principles of vector space, matrix and vector operation, and linear transformation. Calculus
Automotive Mathematics Basic differential, fundamental integral, Taylor series, differential equation basis, Laplace transform, Z transform, Fourier series, vector field, etc.
Mathematics for the 3rd and 4th Major Course.
Calculus

4th Industrial Revolution Basic (3 courses)

Introduction to Artificial Intelligence, Computational Thinking, Programming for Artificial Intelligence

Course Description Prerequisite
Introduction to Artificial Intelligence This course deals with the basic knowledge of artificial intelligence and pattern recognition. Computer Programming, Calculus, Statistics for Big Data Analytics, Linear Algebra
Computational Thinking This course aims to provide the ability to solve problems in various fields efficiently and systematically through computing thinking. Especially, the main interesting is Python programming techniques in this course. Based on this, we will develop various posture problem solving abilities through simple control of EV3 and other machine learning. Basic Software Engineering
Programming for Artificial Intelligence The course deals with implementations of SW using artificial intelligence and pattern recognition knowledge learned from the introduction to AI. Introduction to Artificial Intelligence

4th Industrial Revolution Major (8 courses)

Future Automotive Engineering, Intelligent Vehicle, Instrumentation and Analysis, Automatic Control, Deep Learning, Reinforcement Learning, Infortainment, Autonomous Driving Project

Course Description Prerequisite
Future Automotive Engineering This course aims to understand the latest technology trends related to future automobiles, such as electric cars and autonomous vehicles, based on existing knowledge of automotive engineering, and to understand the related technology and concepts Automotive Engineering
Intelligent Vehicle The course aims to understand the latest technology trends related to intelligent automobile (smart car) such as autonomous driving and ADAS system, and to develop ability to design system packaging of intelligent automobile. Automotive Engineering, Future Automotive Engineering
Instrumentation and Analysis The course introduces instrumentation principle and measurement system, various transducers, amplifiers, filters, data acquisition and analysis, PC application measurement theory.
Automatic Control The purpose of the course is to understand the fundamental concepts of frequency response, system analysis, etc., and to understand basic control theory such as PID control. Automotive Mathematics, Linear Algebra
Deep Learning It deals with deep running as flowers of artificial intelligence. Convolutional Neural Network and Recursive Neural Network are mainly concerned. Computational Thinking, Programming for Artificial Intelligence
Reinforcement Learning Students will learn Deep Q-learning and various reinforcement learning algorithms that can solve problems using in-depth neural networks. Deep Learning, Computational Thinking
Infortainment Audience will learn how the information and entertainment service using the vehicular networks can be done through the Internet connected to the outside world. Linear Algebra, Statistics for Big Data Analytics, Vehicular Communication
Autonomous Driving Project Based on the signal information coming from various autonomous sensors, we will implement autonomous driving using software such as deep running. Intelligent Vehicle, Deep Learning, Autonomous Deriving Sensor, Computer Programming

Automotive Engineering Basic (19 courses)

Basic Experiment of Vehicle I,II, Automotive Engineering, Electrical and electronic circuits I,II, Automotive Dynamics, Power Electronics, Software Engineering for Vehicle, Automotive Engineering Practice I,II, Digital Logic Circuit, Automotive Signal Processing, Embedded System I,II, Vehicular Motor Control, Automotive Security, Vehicular Communication, Internship I,II.

Course Description Prerequisite
Basic Experiment of Vehicle I This course allows to know progressively from tool usage to engine, electric, and chassis parts for automobile basis.
Basic Experiment of Vehicle II
Automotive Engineering Practice I It aims to develop capacity through hands-on practice through theoretical content by understanding the basic structure and principles of automobiles through the theory and practical training necessary for structural and maneuvering in automobiles where maneuverability is essential, and developing automobile culture that has the ability to adapt to field work.
Automotive Engineering Practice II
Automotive Engineering This course aims to develop basic knowledge about automobile engineering and help to understand overall automobile majors. This lecture introduces the theoretical lectures on automobile engineering and the actual automobile manufacturing process.
Electrical and electronic circuits I This course deals with circuit-related physical units such as current, voltage, power, etc., basic knowledge of circuit components, and various theoretical knowledge necessary to construct and analyze circuits. Calculus, Linear Algebra
Electrical and electronic circuits II
Power Electronics Power electronics is a field that converts and controls electric power by power semiconductor switching device. As a typical application field, there is a remarkable development such as general industrial field, transportation transportation field, electric power field, household electric appliance field. Here, as faster switching devices are developed, it is anticipated that applications will be increased in a wider range. Electrical and electronic circuits I, II, Electric Machinery
Software Engineering for Vehicle Based on the basic programming techniques learned in specialized basic software engineering, various SW techniques applied to real vehicle design and implementation are studied. Basic Software Engineering, Linear Algebra
Automotive Dynamics This course aims to understand kinematics basic theory, understand mathematical / physical modeling of vehicle longitudinal, lateral and vertical motions. Automotive Physics I, Automotive Engineering
Digital Logic Circuit We learn the differences between analog signals and digital signals, basic circuits using digital ICs, and apply the functions of digital ICs.
Automotive Signal Processing This course deals with signal processing techniques using input circuit and operational amplifier, modulation, non-modulated signal, filter, etc., as well as the theory and practice of how it is done in real vehicle. Calculus, Linear Algebra, Automotive Mathematics
Embedded System I It aims to understand the components and functions of embedded systems embedded in intelligent and experimental vehicles, to learn about embedded SW and OS, and design simple embedded system configuration according to requirements. Future Automotive Engineering, Intelligent Vehicle, Computer Programming
Embedded System II
Vehicular Motor Control We Learn about software control methods used in vehicle motors and motors. Basic Software Engineering, Linear Algebra
Automotive Security In this lecture, we will find out what kind of measures there are if there is a hacker's attack through the communication network inside or outside the vehicle. Statistics for Big Data Analytics, Vehicular Communication
Vehicle Communication We learn how inter-vehicle communication based on data communication and networking can be achieved through real vehicle communication, in case of emergency prevention, autonomous driving, and infotainment service and so on. Calculus, Linear Algebra, Statistics for Big Data Analytics
Internship I Recognize the importance of personal role in the company, we conduct company's important task execution process and harmonious in-house activity training with colleagues.
Internship II