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음악교육대학원학업계획서 음악대학원연구계획서 합격샘플+면접 음악교육학과대학원자기소개서,서울대학교음악교육대학원 학업계획서,이화여대음악대학원 연세대
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미국의 가족지원정책
미국의 가족지원정책
한국과 미국의 장애인 가족지원정책 비교(한국,미국,장애인 가족지원정책, 한국장애인, 미국장애인, 외국장애인, 서비스, 장애인가정, 해외장애가정)
미국 유럽 국제화지원
[중소벤처기업창업] 중소벤처기업창업의 개념, 중소벤처기업창업의 절차, 중소벤처기업창업시 인력지원제도와 조세지원제도, 중소벤처기업창업시 규제완화지원제도와 기타지원제도, 미국의 중소벤처기업창업지원 사례 분석
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미국 대학원 지원_SOP (Statement Of Purpose)_Grad Admissions_UVA_Data Science_Proofreading Service Verified에 대한 자료입니다.
본문내용
I knew that I was on the brink of discovering a method to streamline my work, but I was already facing analytical challenges. For starters, I was almost completely dependent on the companys internal data, and it was very difficult to decide where and how to find relevant, accurate data from credible sources outside the company. Next, analyzing data and information that continuously changed or was affected by too many factors, such as the performance and well-functioning of newly purchased machinery, was problematic because such information was hard to standardize. Finally, I needed a way to gather the necessary data automatically because mining data manually is time consuming and inefficient.
I unexpectedly found a potential solution for all of these issues while I was fulfilling my task at one of my suppliers, General Electric (GE). I was there because I was working on a power plant project that involved a gas turbine that needed to be examined. Once I arrived, I was surprised to learn about the company’s application of data collection and analytics to the turbine. After speaking to its data scientist, I learned that sensors were installed to collect real-time data, which enabled GEs data scientists to remotely monitor the equipments performance from a centralized data center and improve its efficiency by optimizing the turbines system. Based on this encounter with GEs smart features, I began exploring the potency of data science. The connection between data and machine and the utilization of valuable information derived using analytical data was an innovation that could help me revolutionize my analytical methods. In order to do so, I am well aware that there is much I need to learn. Once I realized that data science is the key to overcoming my current analytical limitations, I became determined to learn more about statistics, mathematics, and computer science as well as attain more sophisticated data mining, quantitative, and analytical techniques. It is for these purposes that I now aspire to pursue a graduate degree in data science.