The Big Data Theory Workshop

We are a group of students with the aim of supporting electrical engineering and computer science students in order to reach their full potential in academic and social life. How do we achieve this?  By helping them further in their education with our technical events and by helping them get in touch with the industry with our industry based events. We are located in Budapest, but we are part of a network of Local Committees spread in the universities all over Europe. And what unites us? The shared passion to grow and help others grow! :)

MAVE - EESTEC LC Budapest

The Big Data Theory is a week-long workshop to introduce Big Data and Data Science to our Hungarian and international participants. During the event you will: • get a comprehensive picture on Data science, Data mining, and Machine Learning • understand the process of handling wast amount of data and finding patterns at the same time. • work on a hands-on project task by the largest bank in Hungary Moreover, our purpose is to offer a general way of thinking for the participants so that they can tackle their challenges with ease in this field. The workshop will consist of four different programme blocks. Participants will learn about the various areas of Big Data during the lectures in the morning. They will also form groups to work together on the given project task. At the end of the workshop, each group will present its results and solutions for the problem. There are two ways to take part on the workshop: • [FULL-TIME]: You will work on the project task during the week. You can apply with a team or if you don't have a team, we will find one for you! 
APPLY AS A FULL-TIME PARTICIPANT BEFORE 24 SEPTEMBER 20:00 TO GET A FREE EVENT T-SHIRT!
• [VISITOR]: If you can't or don't want to take part on the whole workshop, you can attend only the lectures.
 
SCHEDULE
* Obligatory for full-time participants.
MONDAY (2nd October)
9:00 - 9:20 - Opening ceremony*
9:20 - 9:40 - Dankó Zoltán (OTP Bank): Innovation and development in the era of the Digital age*
9:40 - 10:00 - Project task handout.*
10:00 - 11:45 - Asztalos Áron & Lotfi Majid (OTP Bank): Average income prediction by location using Machine Learning in Python*
14:30 - 18:00 - Horváth András: Demonstations and presentations supporting the workshop project task*
<UL>
<LI>What is machine learning</LI>
<LI>Classification and regression problems</LI>
<LI>Step to solve practical problems: Data collection, Filtering and analysis, Model building, Model validation, Cross-validation</LI>
<LI>Examples of machine learning models for regression : Gradient tree boosting, Neural Networks etc...</LI>
</UL>
 TUESDAY (3rd October)
PCF (People Come First) - Data Mining day
9:00 - 11:00 - Balázs Hodossy (PCF): Data science: The place of data science in Big Data, data analization methods, prediction basics, SQL, a little Python
<UL>
<LI>A practice based approach to the foundations of BigData</LI>
<LI>History of datascience</LI>
<LI>Foundations of statistics and probability (among others: useful probabilistic ideas, possible errors in model construction)</LI>
<LI>Introduction to the tools used in BigData analysis (In Python 3.6 and SQL; No prior knowledge of SQL is required and minimal previous Python experience is enough.)</LI>
<LI>Python 3.6 is required</LI>
</UL>
11:30 - 13:30 - Thinking together: simple exercises helping to understand the practical and theoretical aspects of the methodology of data processing 
<UL>
<LI>Several exercises to be solved in groups of 5-6 people and then a short presentation of the ideas found.</LI>
</UL>
14:30 - 18:00 Data analysis workshop 
<UL>
<LI>A 3.5 hour-long coding session</LI>
<LI>Several different exercises in BigData analysis (textual or graphic data)</LI>
<LI>Exercises to be solved in groups</LI>
<LI>The lecturer will be at Your disposal for questions</LI>
<LI>Python 3.6 is required</LI>
</UL>
 WEDNESDAY (4th October)
11:15 - 12:00: I. Horváth István (Eutecus HU Kft.): Video and Data Analytics for Smart City Applications, II. Botos Csaba (Eutecus HU Kft.): Generative Deep Learning Models
12:30 - 13:30: Judit Villányi (Starschema): Data visualization with Tableau/ How to create nice decision supporting visualization fast
Hero video: <A HREF="https://www.tableau.com/#hero-video" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">https://www.tableau.com/#hero-video</A>
15:00 - 16:30 - Zoltán Kurai (Black Swan): Social media text analization 
<UL>
<LI>Text analization/text mining</LI>
<LI>Social media as BigData</LI>
<LI>One application: Show me your tweets and I will tell you where you live!</LI>
</UL>
 
THURSDAY (5th October)
9:00 - ∞ (as you wish) - Hackathon: Working on the workshop project task.*
 
FRIDAY (6th October)
2:00 - Deadline for submiting your project task's results. 
9:00 - 13:30 - Presentation of the projects.*
14:30 - 18:30 - Closing ceremony and awards.
 
You can find more information on the website of the event: <A HREF="https://l.facebook.com/l.php?u=http%3A%2F%2Fbigdata.eestec.hu%2F&h=ATMpglwqVWDhQAmD_pwbmB-kCVJI_UgmXrhZ_xitY68S2Em25QRmbBqDFaY6h2wwAyU_DRmJQAP6a_bg4XSmB-5fP5zcbsO0MOEJyeeprQD5jlfB8zV8JFfgFptD7MYfxUMLxPLgtZAkkhcJTFZmNuAaj8tlSD3AFaBSq-hTlJz0DWA" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">http://bigdata.eestec.hu/</A>
 
FAQs
How can I contact the organizer with any questions? <A HREF="mailto:daniel.benyei@eestec.hu?Subject=TheBigDataTheory%20WS" TARGET="_top" REL="nofollow noopener noreferrer">daniel.benyei@eestec.hu</A>, <A HREF="mailto:kinga.meszaros@eestec.hu?Subject=TheBigDataTheory%20WS" TARGET="_top" REL="nofollow noopener noreferrer">kinga.meszaros@eestec.hu</A>, <A HREF="mailto:dominika.nagy@eestec.hu?Subject=TheBigDataTheory%20WS" TARGET="_top" REL="nofollow noopener noreferrer">dominika.nagy@eestec.hu</A>, <A HREF="mailto:jozsef.mak@eestec.hu?Subject=TheBigDataTheory%20WS" TARGET="_top" REL="nofollow noopener noreferrer">jozsef.mak@eestec.hu</A>
Who can participate in this event? Even tho registration is open to everyone, we expect engineering students with at least beginner programming experience to apply.

OTP Fáy András Foundation

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