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  4. Data Science in the Era of Big Data

Seminar: Data Science in the Era of Big Data

Content

Data has supported research since the dawn of time, but recently there has been a paradigm shift in the way data is used.  Today researchers and practitioners are mining data for patterns and trends that lead to new hypotheses.  This shift is caused by the huge volumes of data available from, e.g., social media websites, web query logs, sensors, and medical devices. ”Big Data” has been established as an umbrella term to cover such high-volume and complex data. In this seminar, we cover recent topics of Data Science in the era of Big Data. The core question we tackle is: How can we efficiently extract knowledge from large and complex data? To study this question, the seminar comprises two aspects: On one hand, we discuss modern computing frameworks for large-scale data analytics such as Apache Hadoop, Spark, and Giraph. On the other hand, we review models and algorithms for pattern detection in large data. In particular, we will focus on applications such as anomaly detection and community discovery in e-commerce and social media data. This seminar is ideal for students interested in data science, data mining, large-scale data analytics, and/or machine learning. It is also a good starting point for writing a Bachelor/Master thesis on related topics. Basic knowledge in data mining and/or machine learning is helpful but not mandatory.

Structure of the seminar

Each student selects a specific topic (computing framework/mining algorithm), which he/she will present in the seminar. Additionally, a seminar paper summarizing the topic needs to be submitted before the presentation (approximately 3-4 pages for Bachelors and 5-6 pages for Masters; a template for the reports will be provided).

Organization

Please register for the seminar by sending an e-mail to data.science.tum(at)gmail.com. The e-mail should contain your contact information, your program of study, and (if applicable) your knowledge/experience in data science and related topics. The deadline for registration is May 15th, 2015. The seminar will be held as a block seminar; either at the end of the lecture period or during the semester break. The exact date will be coordinated with all seminar participants. Furthermore, there will be a mandatory kick-off meeting taking place in May. Again, the exact date of the kick-off will be discussed with all participants. The seminar is open for Bachelor and Master students. Reports can be written in English or German. English presentations are preferred; however, only recommended if you are proficient in English conversation. For further information, please contact Dr. Stephan Günnemann.

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Informatics 26 - Data Analytics and Machine Learning


Prof. Dr. Stephan Günnemann

Technical University of Munich
TUM School of Computation, Information and Technology
Department of Computer Science 
Boltzmannstr. 3
85748 Garching
Germany

Secretary's office:
Room 00.11.057
Phone: +49 89 289-17256
Fax: +49 89 289-17257

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