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MCS 226 Data Science and Big Data (From MCA Programme of IGNOU) | Guess Papers of IGNOU

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MCS 226 Data Science and Big Data (From MCA Programme of IGNOU) | Guess Papers of IGNOU

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Comprehensive guide to data science and big data for MAEC students. Includes exam-focused content and guess papers for effective exam preparation.
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  • Covers fundamental concepts of data science and big data.
  • Explores data analysis techniques and tools.
  • Provides 50-60 pages of exam-centric content.
  • Includes important questions for IGNOU exams.
Category : MASTER‘S DEGREE PROGRAMMES
Sub Category : Master of Arts (Economics)(MAEC)
Products Code : MAEC-MEC-S4-A-5.21
HSN Code : 490110
Language : English, English
Author : BMAP EDUSERVICES PVT LTD
Publisher : BMAP EDUSERVICES PVT LTD
University : IGNOU (Indira Gandhi National Open University)
Pages : 50
Weight : 157gms
Dimensions : 21.0 x 29.7 cm (A4 Size Pages)



Details

MCS 226 Data Science and Big Data is an indispensable resource for MA Economics students seeking to understand the principles and applications of data science and big data analytics. This guide offers comprehensive coverage of fundamental concepts such as data mining, machine learning, data visualization, and big data frameworks. It explores various data analysis techniques and tools essential for handling large datasets and deriving meaningful insights. With 50-60 pages dedicated to exam-centric guess papers, this book ensures thorough preparation by focusing on important questions frequently asked in IGNOU examinations. By utilizing this resource, students can enhance their data analytical skills, apply advanced data science methods to economic data, and excel in their MAEC examinations.

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The IGNOU solved assignments and guess papers provided on this platform are for reference purposes only and should not be used to engage in educational dishonesty. These materials serve as learning and study tools and are not intended for submission as original work. Users are responsible for using these materials ethically and in accordance with their educational institution's guidelines. We do not assume liability for any misuse or consequences resulting from the use of these materials. By accessing and utilizing these resources, users agree to this disclaimer.

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