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Fusion Software Education Program - Qualifications, Application Process, and Overseas Opportunities

This overview provides information on the Fusion Software Education Program, including eligibility criteria, application process, and available opportunities for undergraduate and graduate students in relevant fields. It also highlights partnerships with prestigious universities and industry leaders for overseas projects and internships.

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Fusion Software Education Program - Qualifications, Application Process, and Overseas Opportunities

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  1. CSIDGlobalProgram 2019년 융합소프트웨어교육원

  2. Overview

  3. 융합소프트웨어교육원

  4. 지원자격및선발방법 학부프로그램:SW관련학과및SW연계전공자 ¥ 컴퓨터공학과,멀티미디어공학과,정보통신공학과,7개SW연계전공재학생(휴학생제외) 2020년2월이후졸업예정자(2019년8월졸업예정자제외) ¥ ¥ 대학원프로그램: ¥ 대학원인텔리전스학과2019년9월또는2020년3월진학예정인동국대4학년 동국대대학원재학생(SW전공자또는SW개발가능자,박사과정우대,지도교수추천필수) ¥ ¥ 서류평가및면접 ¥ 학부:해외교육에대한의지,프로젝트수행능력등 대학원:대학원진학의지및석사과정이수능력,연구능력등 ¥ ¥ 모든프로그램은변경되거나취소될수있음 ¥ 융합소프트웨어교육원

  5. 지원및전형절차 대학원프로그램 ¥ 제출기한:2019.4.10(수)17:00 ¥ ¥제출방법:온라인접수후추가서류는E-mail송부 ¥제출처:https://forms.gle/8g1zzz4r34muETwq5 ¥면접일정:2018.4.11(목)또는4.12(금)(서류합격자개별이메일통보) ¥합격자개별이메일통보(4.16까지) 학부프로그램–중국베이징프로그램을제외한나머지 ¥ 제출기한:2019.4.15(월)17:00 ¥ ¥제출방법:온라인접수후추가서류는E-mail송부 ¥제출처:https://forms.gle/xiYb2X3CPrczvvfx7 ¥면접일정:2018.4.17(수)또는4.18(목)(서류합격자개별이메일통보) ¥합격자개별이메일통보(4.19까지) 융합소프트웨어교육원

  6. Overview 학부 ¥ NationalUniversityofSingapore ¥ ¥http://www.nus.edu.sg/ ¥PurdueUniversity ¥http://www.purdue.edu/ ¥HeadStartSiliconValley,Inc. ¥http://www.headstartsv.com ¥ActilityThingPark ¥http://www.thingpark.com/ 대학원 ¥ NationalUniversityofSingapore ¥ ¥RiskManagementSolutions,Inc. ¥http://www.rms.com 융합소프트웨어교육원

  7. 학부&대학원 학부프로그램 ¥ Capstone&Internship ¥ ¥학점인정–Internshiponly ¥영어논문작성–Capstoneonly 대학원프로그램 ¥ 인텔리전스학과진학예정학부생대상 ¥ 융합소프트웨어교육원

  8. 인텔리전스학과 융합소프트웨어교육원 일반대학원 ¥ ¥ 3개전공 ¥지능공학:Software(AI,BigData) ¥의료지능:의료+AI융합전공 ¥인문/예술/사회과학지능:인문/예술/사회과학+AI융합전공 ¥ 재학중전액장학금지급 ¥ ¥재학중해외학술대회참가지원등 학과설명회는추후따로있을예정 융합소프트웨어교육원 ¥

  9. Procedure ¥Preparation duringthe1stsemester Obtainbaseknowledge ¥ ¥Workand/orlearnintheU.S.,Singapore,orChina duringtheSummer ¥Followupduringthe2ndsemester Submitprojectreport ¥ ¥Writepapersorpatents 융합소프트웨어교육원

  10. QualificationandRequirements 전공 ¥ ¥컴퓨터 ¥정보통신 ¥멀티미디어 ¥*소프트웨어연계전공 ¥English ¥Motivation ¥Responsibility 융합소프트웨어교육원

  11. 학부

  12. NationalUniversityof Singapore

  13. NUS–ranked10thintheworld 융합소프트웨어교육원

  14. SummerWorkshop http://www.comp.nus.edu.sg/~sws/ ¥ 융합소프트웨어교육원

  15. PurdueUniversity

  16. PurdueUniversity •소 재지:미국인디애나주WestLafayette(본교) •개교:1874년 •유형:공립종합대학 •학생수:39,228명(2014)/•전임교원:3,075명 •대외평가:미공과대9위,컴퓨터공학11위(17년USNews) -세계74위,미26위(QS대학평가(17년),ComputerScience) 융합소프트웨어교육원

  17. 추진방향 美현지학생,현지엔지니어와같이프로젝트를진행하면서선진화된문제해결방법,프로젝트계획/관리등 을학습 해외우수대학이갖는인프라및기술적강점을적극적으로활용함으로써국내에서는경험할수없는다양 한기술구현을추진 ¥ ¥ 구분 기본 프로그램 (8주) 캡스톤디자인프로젝트 •신상품개발을고려한 세분화된주제를학생들이 선택하여팀구성후 프로젝트수행 •프로토타입개발후 최종평가실시 전공이론교육 •학생들의흥미와관심, 프로젝트주제등 부합하는전공과목수강 •청강과목:Computer Information&Technology, ComputerScience GraphicsTechnology등 수강 세미나및영어교육 •대학인근지역의 기업멘토를활용한 기술코칭및최신 ICT기술트렌드교육 •LafayetteAdult ResourceAcademy 영어ELS및TOEFL 수강(주4일) 융합소프트웨어교육원

  18. 프로젝트및현지프로그램상세 프로젝트 ¥ SW개발프로젝트12개*과제별주요내용설명 SW분야:AI,Mobile,HealthcareSW,VR,SafetyandSecurityRobotics 참여기업:HewlettPackardEnterprise,Intel,InteractiveIntelligence등8개 참여교수:EricMatson교수등7명/현지학생:학부생,석/박사학생등14명 프로젝트팀구성 팀구성:수행과제별로국내학생(4-5명),지도교수(1명),현지학생(1명),기업멘토(1명)등7~8 명으로구성예정 팀구성은참여학생들의영어성적,관심주제등을고려하여현지지도가구성 프로젝트수행:팀별로프로젝트제안서,추진계획,주차별수행보고서,최종결과보고서,결 과발표PPT등 ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ 전공과목청강:현지참여교수개설과목2과목이상청강의무 ¥ 전공과목청강:퍼듀대에서현지상세자료추후안내예정 ¥ 영어수업수강:프로젝트수행을위한영어회화능력향상 ¥ LafayetteAdultResourceCenter:LARA(Morning8:30-11:30,11:30-1:00) 융합소프트웨어교육원 ¥

  19. 융합소프트웨어교육원

  20. 융합소프트웨어교육원

  21. 융합소프트웨어교육원

  22. Actility-ThingPark

  23. ThingPark 중국,베이징 멀티미디어공학과주관 ¥ ¥ 융합소프트웨어교육원

  24. 대학원과정

  25. NationalUniversityof Singapore

  26. ResearchTopic AI-basedautomaticclassificationofcrowdsourcedimageswith noise ¥ Objective1:Noisecorrectionofimagelabelingincrowdsourcing ¥Designnovelmachinelearningbasedsolutionstoidentifythetrue (accurate)labelsofcrowdsourceddata.Theapproachwillinvestigate andaddressthemajorfactorscausingimprecisioninthelabels collectedduringthecrowdsourcingoperation. ¥ ¥ Objective2:Imageclassificationwithimprovedinterpretabilitythrough weaklysupervisedlearning ¥Designweaklysupervisedlearningmodelsforimageclassification whereonlylabelsatacoarse-grainedlevelareoriginallyprovided.The approachwilldesignmethodstoprovidethefiner-grainedlevellabels thatallowexplainability.Wewillalsoimplementaplatformtovisualize thelearningresults. 융합소프트웨어교육원 ¥

  27. RMS & GLOBAL TECHNOLOGIST DEVELOPMENT PROGRAM JosephKim seniordirectorofmodel development

  28. RMS FoundedatStanfordUniversityin 1988 Solelyfocusedonindependent viewofriskquantificationandrisk management •Independentreinsuranceindustry •SubsidiaryofDMGT •Providecatastropheriskmanagement andquantificationsolutionstothe$1 trilliondollarglobalinsuranceindustry RISK.MANAGED.

  29. OURJOURNEY

  30. OurmissionistocreateamoreresilientandsustainableglobalsocietythroughabetterOurmissionistocreateamoreresilientandsustainableglobalsocietythroughabetter understandingofcatastrophicevents. • • • Weleadanindustrythatwehelpedpioneer Ourworkmakesanimpactontheworldatlarge Howweunderstandandmanageriskaffectsus all RMS(One) Aplatformattheheartoftheglobalriskmarket, transforminganindustrytocreateamoreresilient andsustainableglobalsociety

  31. THEPROJECTS •RMSChinaAGRICULTUREAgricultureModelMODELAnalyticalEngineMigration • • • IndiaAgricultureModelAnalyticalEngineMigration RMSprovidesadvancedagriculturalanalyticsandsolutionstogloballeading KRUfinancial–MarketplaceinstitutionsPlatformforEthnicCommunitiesLivingintheUS •OurclientsuseRMSanalyticstoassessfutureyieldforcrops,livestocks,and forestry •Agriculture-relatedfinancialproductmarketopportunityisUS$600billionjustforUS alone

  32. CHINAAGRICULTUREMODELANALYTICALENGINEMIGRATION •CurrentlyCAMisWindowsdesktopapplicationwithmostanalyticalscenarios pre-compiled •Thislimitsflexibility •Basedonprevious-generationtechnology •Theprojectistomigratethecoreanalyticalenginetoournewagriculturemodel analyticalengineplatform •Capableofhandlingbigdataanalyticsworkingwithsimulationof30,000years ofweathervariations •100%cloud-based

  33. INDIAAGRICULTUREMODELANALYTICALENGINEMIGRATION •CurrentlyIAMisWindowsdesktopapplicationwithmostanalyticalscenariospre- compiled •Thislimitsflexibility •Basedonprevious-generationtechnology •Theprojectistomigratethecoreanalyticalenginetoournewagriculturemodel analyticalengineplatform •Capableofhandlingbigdataanalyticsworkingwithsimulationof30,000years ofweathervariations •100%cloud-based

  34. TECHNICALLANDSCAPE §Techstack §ApacheSparkandHadoopecosystemoftechnologies §ScalaandJava §Linux,OSX §AmazonAWSandMicrosoftAzure §Devprocess §Agile,continuousintegrationanddeployment §Agiledevelopment §Githubandgitflow

  35. COREWORKFLOW §Learn §Architectureanddesignoftheplatform §Initialproof-of-conceptofhowtoproceed §Develop §Incremental,steady,high-qualitycodecontribution §Peercodereview §Iterate §Refactorexistingcode §Addnewfeaturesbasedonspecification §Measurableachievementtowardssuccessfulcompletion

  36. Contact 김동호 ¥융합소프트웨어교육원 ¥정보문화관P610 ¥02-2290-1405 ¥dongho.kim@dgu.edu ¥ 융합소프트웨어교육원

  37. Thankyou!

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