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