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    Statistical Modeling for Data Science - Simpliv

    View: 1855

    Website https://www.simpliv.com/machinelearning/statistical-modeling-for-data-science | Want to Edit it Edit Freely

    Category training;webinar

    Deadline: April 24, 2019 | Date: April 24, 2019-May 03, 2019

    Venue/Country: online course, U.S.A

    Updated: 2019-04-22 20:09:15 (GMT+9)

    Call For Papers - CFP

    About this Course

    On the off chance that you are going for a profession as a Data Scientist or Business Analyst at that point looking over your statistics abilities is something you have to do.

    In any case, it's only difficult to begin... Learning/re-adapting ALL of details just appears like an overwhelming undertaking.

    That is precisely why we have made this course!

    Here you will rapidly get the significant details learning for a Data Scientist or Analyst.

    This isn't simply one more exhausting course on details.

    This course is exceptionally pragmatic.

    I have particularly included true models of business difficulties to demonstrate to you how you could apply this learning to help YOUR vocation.

    In the meantime you will ace points, for example, dispersions, the z-test, the Central Limit Theorem, theory testing, certainty interims, measurable criticalness and some more!

    So what are you sitting tight for?

    Select now and enable your profession!

    Basic knowledge

    Just a basic knowledge of high school math

    Interest in Learning Statistical Modelling

    What you will learn

    People working in any numerate field which requires data analysis

    People carrying out observational or experimental studies

    Any one who want to make career in Data Science

    Contact Us:

    simplivllcatgmail.com

    Phone: 76760-08458

    Email: sudheeratsimpliv.com

    Phone: 9538055093

    To read more and register: https://www.simpliv.com/machinelearning/statistical-modeling-for-data-science


    Keywords: Accepted papers list. Acceptance Rate. EI Compendex. Engineering Index. ISTP index. ISI index. Impact Factor.
    Disclaimer: ourGlocal is an open academical resource system, which anyone can edit or update. Usually, journal information updated by us, journal managers or others. So the information is old or wrong now. Specially, impact factor is changing every year. Even it was correct when updated, it may have been changed now. So please go to Thomson Reuters to confirm latest value about Journal impact factor.