[arXiv] BigDataFr highly recommends: Leading Undergraduate Students to Big Data Generation #datascientist #machinelearning #conceptlearning

BigDataFr highly recommends: Leading Undergraduate Students to Big Data Generation

Introduction

« People are facing a flood of data today. Data are being collected at unprecedented scale in many areas, such as networking[14][2][4], image processing[15
][5], visualization[12], scientific computation, data base[17][18], and algorithms. The huge data nowadays are called Big Data.
Big data is an all-encompassing term for any collection of data sets so large and complex that it becomes difficult to process them using traditional data processing applications.(Wikipedia 2015). New technologies and new forms are driving the Big Data development, with the global Internet population g rowing by 6.5% averagely in the past three years and now representing two billion people.
Almost everyone heard the term Big data nowadays. Big Data is used in a wide variety of applications, such as traffic patterns, purchasing behaviors, online video, and real-time inventory management.

Consequently, there is a high demand of job positions on Big Data. In Georgia and Ohio, for example, a critical need exists for a highly qualified information technology (IT) workforce
regarding Big Data. There are over 4,000 vacant IT jobs in Georgia and Ohio that employers cannot readily fill related to Big Data(Monster.com and CareerBuilder.com, 2014). Although almost everyone heard the term Big Data, many people, even undergraduate students in Computer Science major have poor understanding of what Big Data is.

Big Data is critical for students current study and future career; hence many schools are training Big Data to students. However, it is extremely difficult to teach it because: First, manipulating
data sets often requires massively parallel software running on tens, hundreds, or even thousands of servers.
Second, there is no specific Big Data course in most schools. Many instructors met a lot of challenges when they teach Big Data to students. The challenges on teaching a
nd learning Big Data include analysis, capture, search, sharing, storage, transfer, visualization, and privacy violations. In this article, the authors present a unique way which uses network simulator and tools of image processing to train students abilities to learn, analyze, manipulate, and apply Big Data. Thus they develop students hands-on abilities on Big Data and their critical thinking abilities.

The authors work is not merely to introduce Big Data. Rather, their projects incorporated students in concept learning, research design, data collection, data manipulation, analysis, and
problem solving of networking and multimedia.
The authors provided students with two areas of applications.
The first one is on web/mobile. A simulator was provided and student learned how to simplify Big Data in networking to a single computer program. The second one was on image processing.
The authors used novel image based rendering algorithm with user intervention to generate realistic 3D virtual world.
The learning outcomes are significant. »
Read Paper
By Jianjun Yang, Department of Computer Science and Information Systems, University of North Georgia and Ju Shen, Department of Computer Science, University of Dayton
Source: arxiv.org

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