30th Sept. 2016 Les Math du Big Data Day@ENIT-LAMSIN 1

Academic Insights on Teaching Big Data Technologies: Facts and Fallacies

Rim Moussa ENI-CarthageUniversity of CarthageLaTICE Lab

Les Math. des Big Data Day @ ENIT Eng. School-LAMSIN Lab.30th of September, 2016

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Outline

●Big Data Technologies

●Teaching Big Data: facts & fallacies

●French HPC

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Big Data TechnologiesLandscape

It's worth knowing that we teach technologies engineering

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Big Data TechnologiesScope

●Big Data Management Systems

●Data Warehousing and OLAP

●NewSQL Systems

●Real-time Systems

●Hybrid Systems

●Machine Learning

●Information Retrieval

●Infrastructure

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Teaching Big Data Goals

●Students

»Get a good job with no experience

●skills learned in school

●Job market

»Create a start-up

●Facilities? Co-working spaces, sponsorship programs, ...

●Nation

»Research centers

»The valley

»Leading technologies

»ROI

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Teaching Big Data Facts

●CS enrollments are growing

●Learning places

»Coursera: on-line courses from top universities

●Each course: 4-6 weeks + good quality materials (slides,

skilled professors' podcasts, labs) + weekly assignments +

final exam + discussion forums + certification + affordable

prices

» University X

●semester teaching periods + few assignments + few labs +

final exam

●Diploma: Past Maitrise: 7 semesters → Present Eng. schools:

5 semesters

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Teaching Big DataFrench Job Market 1/2

Looking for skilled and senior profiles

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Teaching Big DataFrench Job Market 2/2

Looking for skilled and senior profiles

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Teaching Big Data Curriculum and Study programs

● First,●CS Theory; OS, data structures, algos, discrete math, stat,

networks, AI, security, compilation & language theory ….●Script languages and prog. languages●Software engineering, RDBMS, Web Dvpt Frameworks

●Master Program●Distributed {computing, data management, architectures}

Real-time systems, green computing + Machine Learning + Artificial Intelligence + Data Warehousing, Information retrieval + GIS + {ML, DW, OLTP, IR, AI, GIS} at scale

●Programming Languages big data, frameworks THEN some Big Data Technologies

●Labs: HPC platforms●Senior profiles hold a PhD in High Performance Computing

(distributed systems) + other domains skills such as Machine Learning, Data Warehousing ….

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Teaching Big Data Mind about ...

●Fallacy #1: HPC community

●Fallacy #2: Cost of HPC platforms

●Fallacy #3: Inter-disciplinary Master Programs

●Fallacy #5: Job Market

●Fallacy #6: ROI

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French HPC Implementation

●Grid5000

»Since 2003

●Master programs

»Master STS Mention HPC, Simulation Scientific Computing

at Lille 1 University

●Grant program: 10.000€ per year

●Computing facilities: 45Tflops cluster

●Research projects

»Type: PIA, ANR, Region, CIFRE

»Gov. Instances: Inria, CNRS, CEA, IPGP, …. CHU

»Inria start-ups

●Tunisian implementation?

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References

●A. Gilbert and A. Rudra (Colorado University USA)

Teaching Theory in the time of Data Science/Big Data

2016

»Thorough survey study of 24 CS B.Sc. American

Universities

●C. Mohan (IBM fellow USA)

Big Data: Hype and Reality

2013-2015

»distill reality from the hype!

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Thank you for your Attention

Q & A

Academic Insights on Teaching Big Data Technologies: Facts and Fallacies

Rim Moussa

30th of September, 2016@ENIT Eng. School – LAMSIN Lab.