수석 콘텐츠 개발자
Jonathan은 데이터 및 분석 온라인 교육에 주력하는 Microsoft의 콘텐츠 개발자 및 프로젝트 관리자로 일하고 있습니다. 그는 Microsoft Dynamics NAV에서 Windows Active Directory에 이르기까지 개발자 및 IT 전문가 대상 교육에 참여했습니다.
Microsoft에 오기 전에 Jonathan은 Microsoft Dynamics NAV 솔루션을 구현하는 Microsoft 파트너의 컨설턴트로 일했습니다.
Seth는 Microsoft R Server를 사용하는 클라이언트 교육 및 컨설팅을 전문으로하는 Microsoft의 데이터 과학자입니다. 그의 과거 작업에는 R 및 MRS를 사용하도록 데이터 과학자 팀을 교육하고, MRS가 빅 데이터 아키텍처에 어떻게 적합한지 보여주고, SAS와 같은 도구에서 R 및 MRS 로의 마이그레이션 지원, R 성능 최적화 등이 있습니다. Microsoft에 입사하기 전에 Seth는 2015 년 5 월 Microsoft가 인수한 R 기반 빅 데이터 및 분석 회사 인 Revolution Analytics에서 분석 컨설턴트로 일했습니다. 또한 Seth는 American Express 및 Saks Fifth에서 이전 작업에서 마케팅 및 고객 분석 경험이 있습니다. 수단. 그는 열정적 인 "R-vangelist", 열렬한 아웃 도어맨 (호수와 산에 가까워지기 위해 시애틀로 이주), 아마추어 글로브 트로터입니다.
About this course
This course is part of the Microsoft Professional Program Certificate in Data Science and the Microsoft Professional Program Certificate in Big Data..
The open-source programming language R has for a long time been popular (particularly in academia) for data processing and statistical analysis. Among R's strengths are that it's a succinct programming language and has an extensive repository of third party libraries for performing all kinds of analyses. Together, these two features make it possible for a data scientist to very quickly go from raw data to summaries, charts, and even full-blown reports. However, one deficiency with R is that traditionally it uses a lot of memory, both because it needs to load a copy of the data in its entirety as a data.frame object, and also because processing the data often involves making further copies (sometimes referred to as copy-on-modify). This is one of the reasons R has been more reluctantly received by industry compared to academia.
The main component of Microsoft R Server (MRS) is the RevoScaleR package, which is an R library that offers a set of functionalities for processing large datasets without having to load them all at once in the memory. RevoScaleR offers a rich set of distributed statistical and machine learning algorithms, which get added to over time. Finally, RevoScaleR also offers a mechanism by which we can take code that we developed on our laptop and deploy it on a remote server such as SQL Server or Spark (where the infrastructure is very different under the hood), with minimal effort.
In this course, we will show you how to use MRS to run an analysis on a large dataset and provide some examples of how to deploy it on a Spark cluster or a SQL Server database. Upon completion, you will know how to use R for big-data problems.
Since RevoScaleR is an R package, we assume that the course participants are familiar with R. A solid understanding of R data structures (vectors, matrices, lists, data frames, environments) is required. Familiarity with 3rd party packages such as dplyr is also helpful.
Meet the instructors
Senior Content Developer
Jonathan works as a content developer and project manager for Microsoft focusing in Data and Analytics online training. He has worked with trainings for developer and IT pro audiences, from Microsoft Dynamics NAV to Windows Active Directory.
Before coming to Microsoft, Jonathan worked as a consultant for a Microsoft partner, implementing Microsoft Dynamics NAV solutions.
Seth is a data scientist at Microsoft who specializes in training and consulting clients who use Microsoft R Server. His past work includes training teams of data scientists to use R and MRS, showing how MRS fits in the big-data architecture, and helping with migration from tools such as SAS to R and MRS, and optimizing R performance. Before joining Microsoft, Seth worked as an analytics consultant at Revolution Analytics, the R-based big data and analytics company that was acquired by Microsoft in May 2015. Seth also has experience in marketing and customer analytics from prior jobs at American Express and Saks Fifth Avenue. He is a passionate "R-vangelist", an avid outdoorsman (who moved to Seattle to be close to lakes and mountains), and an amateur globetrotter.
키워드 : 데이터사이언스, 데이터 사이언스