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Dette kurset har ikke oppført noen dato for studiestart. Bruk skjemaet under for å kontakte leverandør for nærmere informasjon.
K-tech er et kompetansesenter på Kongsberg som startet opp i 2008 med Kongsberg Defence & Aerospace, Technip FMC og GKN Aerospace som våre eiere. Vi er en kursleverandør som tilbyr kvalitetssikrede kurs innenfor en rekke sentrale områder som er etterspurt av industrien i Norge.
This 5-day class is taught by Rafal Lukawiecki. Some of the topics will be introduced at level 200, without requiring you to have data science prerequisites, on the first day. However, as the class progresses, the level of the training will quickly increase to 300 and 400.
You will learn machine learning, data mining, some statistics, data preparation, and how to interpret the results. You will see how to formulate business questions in terms of data science hypotheses and experiments, and how to prepare inputs to answer those questions. We will cover common issues and mistakes, how to resolve them, like overtraining, and how to cope with rare events, such as fraud. At the end of this course you will be able to plan and run data science projects. As a practicing data miner, Rafal will also share his decade of hands-on experience while teaching you about Azure Machine Learning (Azure ML) which is the foundation of Cortana Analytics Suite, and its highly-visual, on-premises companion, the SQL Server Analysis Services Data Mining engine, supplemented with the free open source and Cortana’s Revolution Analytics R software. We will use some Excel, however, most of our time will be spent in ML Studio, some in R, RStudio, SSDT, SSMS, and the Azure Portal.
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Although there are no formal prerequisites to attend this course because everyone will benefit from the lectures and the discussions, you will find that if you want to follow the demos and examples on a PC a certain knowledge of SQL Server Data Tools and Excel as well as basic knowledge of writing SQL queries will help. It will also help if you have some experience of analytical projects.
Best of all: prepare questions that you would like to answer using predictive analytics and machine learning.
Analysts, power users, predictive and BI developers, database and other professionals who wish to embrace machine learning, budding data scientists, consultants.Påmeldingsskjema Send meg gratis info