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  • Department of Digital Media Communication Engineering
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Department of Digital Media Communication Engineering

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
AIM5014 Theory of Digital Integrated Circuit Design 3 6 Major Master/Doctor 1-4 Artificial Intelligence - No
This coursecoversstructuresandoperationalprinciplesofCMOStransistorsanddigitalcitcuits(INV,NAND,NOR,LATCH,CurrentMirror),computationofsizinganddelays,FlashA/Dconverter.
AIM5015 Theory of Embedded Systems 3 6 Major Master/Doctor 1-4 Artificial Intelligence - No
Thiscourseintroducestheessenceofembeddedsoftwareandprogrammingskillsforembeddedsystemdesign.Itcoversthesubjectsondatastructureandsystemprogramming,embeddedsystemprogrammingenvironment,overviewofrealtimeOS,taskandscheduling,synchronizationandcommunication,linuxdriverdevelopmentenvironment,andlinuxdevicedriverprogramming.
AIM5016 Advanced Computer Architectures 3 6 Major Master/Doctor 1-4 Artificial Intelligence - No
Thefocusofthecoursewillbeonhigh-performanceprocessorandmemoryarchitectures.Wewillexplorevarioustechniquesdesignedtomaximizeparallelismandimproveperformance.Wewilllookattheinfluenceoftechnologyonprocessorandmemoryarchitecturesandhowthatmayaffectfutureprocessordesigns.Theemphasisisonthemajorcomponentsubsystemsofhighperformancecomputers:pipelining,instructionlevelparallelism,memoryhierarchies,input/output,andnetwork-orientedinterconnections.Studentswillundertakeamajorcomputingsystemanalysisanditsrelatedproject.
AIM5017 NPU Design 3 6 Major Master/Doctor 1-4 Artificial Intelligence - No
Recently, the development of artificial intelligence technology has increased the necessity of highly efficient neural network processor, and neural processing unit (NPU) can be implemented as standalone single chip or multiprocessor system-on-chip (MPSoC). In this course, basic knowledge of integrated circuit, semiconductor technology, and computer architecture is included and oriented to high efficiency NPU design methodology optimized in performance, area, and power efficiency according to the evolution of artificial intelligence technology.
AIM5018 Theory of Analog IC Design 3 6 Major Master/Doctor 1-4 Artificial Intelligence - No
ThiscourseprovideasimulationtechniqueandCMOSdevicemodelingforanalogdesign.Basedonthebasicdesigntechnique,thecoursecoverthefollowingsubjectsformemorydesign,CurrentMirrorCircuit,OP-Ampdesign,ReferenceCircuitDesign,ChargePumpDesign,PLL/DLLdesignandI/OBufferdesign.
AIM5019 Theory of Speech Recognition 3 6 Major Master/Doctor 1-4 Artificial Intelligence - No
Thislessonconsidersspeechrecognitionbasedonpatternrecognition.Mainsubjectsarenatureofspeechsounds,principlesofspeechanalysis,fundamentalsofspeechrecognition,dynamictimewarping(DTW),hiddenmarkovmodel(HMM),neuralnetwork,robustnessinspeechrecognition,andspeechsynthesis.
AIM5020 Theory of Computer Vision 3 6 Major Master/Doctor 1-4 Artificial Intelligence Korean Yes
ThislessondiscussesbasictechnologiesonInput,processinganddisplayingofvisualsignals.Mainsubjectsareimagealgebra,imageenhancementtechniques,edgedetection,thresholding,thinningandskeletonizing,morphologicaltransforms,linearimagetransforms,patternmatchingandshapedetection,imagefeaturesanddescriptors,deepneuralnetworks,andsoon.
AIM5021 Natural Language Processing Theory and applications 3 6 Major Master/Doctor 1-4 Artificial Intelligence Korean Yes
Naturallanguageprocessing(NLP)isoneofthemostimportanttechnologiesoftheinformationage.Understandingcomplexlanguageutterancesisalsoacrucialpartofartificialintelligence.TherearealargevarietyofunderlyingtasksandmachinelearningmodelsbehindNLPapplications.Inthiscoursestudentswilllearntoimplement,train,debug,visualizeandinventtheirownneuralnetworkmodels.Thecourseprovidesathoroughintroductiontocutting-edgeresearchindeeplearningappliedtoNLP.thiscoursewillcoverwordvectorrepresentations,window-basedneuralnetworks,recurrentneuralnetworks,long-short-term-memorymodels,recursiveneuralnetworks,convolutionalneuralnetworksaswellassomerecentmodelsinvolvingamemorycomponent.
AIM5022 Information Retrieval Theory 3 6 Major Master/Doctor 1-4 Artificial Intelligence - No
Information Retrieval (IR) includes the theory and practical techniques for search engines. In this course, we will cover the models and methods for representing, indexing, searching, browsing, and summarizing information in response to a person's information need. In addition, we will deal with recent advances in neural information retrieval models.
AIM5023 Data Mining Theory and applications 3 6 Major Master/Doctor 1-4 Artificial Intelligence - No
Data mining is the process of discovering interesting patterns and relationships in massive data sets. This graduate course will focus on discussing the state-of-the-art data mining techniques which are recently published works at top-tier conferences. Not only the traditional data mining techniques which are basically designed to handle structured data but also more advanced tools/methods for handling unstructured data (e.g., graphs, images, and texts) will be discussed.
AIM5024 Recommendation Systems 3 6 Major Master/Doctor 1-4 Artificial Intelligence - No
A recommendation system is the information filtering system that seeks to predict the rating or preference that a user would give to a target item. In this course, we will cover non-personalized recommender systems, content-based and collaborative techniques. We also cover nearest neighborhood methods and matrix factorization methods. Lastly, we will address the recent advances in recommender systems using deep neural networks.
AIM5025 Intelligent Robot and System 3 6 Major Master/Doctor 1-4 Artificial Intelligence - No
Inordertouserobotsveryefficiently,robotsarerequestedtobeabletoperformalltasksashumanscan.Thiscoursediscussesthetechniqueofsensoranditsapplicationinordertomakerobotsperformtasksintelligently.
AIM5025 Intelligent Robot and System 3 6 Major Master/Doctor 1-4 Artificial Intelligence - No
Inordertouserobotsveryefficiently,robotsarerequestedtobeabletoperformalltasksashumanscan.Thiscoursediscussesthetechniqueofsensoranditsapplicationinordertomakerobotsperformtasksintelligently.
AIM5026 Introduction to Robotic Intelligence 3 6 Major Master/Doctor Artificial Intelligence - No
Robot is defined as an intelligent system connecting sensors and actuators. As an intelligent system, robot is to play a key role for providing necessary services to human by automatically carrying out tasks requiring navigation and manipulation. To this end, robot needs to recognize objects and understand surroundings while reasoning and planning the behaviors necessary for carrying out tasks. Especially, it is essential for robot to be able to obtain its capabilities of recognition and understanding of environments as well as of reasoning and planning of behaviors by learning. This course deals with the fundamentals of robot intelligence on how robot learns for the recognition and understanding of environments as well as for the reasoning and planning of behaviors associated with manipulation and navigation.
AIM5027 Advanced AI-Robot Computing 3 6 Major Master/Doctor Artificial Intelligence - No
ThiscourseteachesbasiccomputerprogramminglanguageandOSenvironmenttoimplementAIalgorithmandRobotControl.ItlearnsLinuxandadvancedc++andPythonprogramminglanguage.OpenCV,OpenGL,Boost,whicharewidelyusedforAIandVision,andNumpy,Matplotlib,andPillowwhicharewidelyusedforlearningalgorithms.AftertheProject,weunderstandthebasicprinciplesofdesigningsuchaprocedurebyunderstandingtheoperatingprinciplesoflearningalgorithmsappliedinvariousfieldsanddefiningnecessaryrequirements.