The Master of science Data Analysis and Pattern Classification of TELECOM SudParis is joint degree with the french DNM (Diplôme National de Master) TRIED "Sciences pour l'Ingénieur, Spécialité Traitement de l'Information et Exploitation des Données" by agreement with "Université de Versailles-Saint-Quentin-en-Yvelines".
This MSc degree is designed to provide the tools allowing processing all types of real data captured by sensors. At the end of the 2-year program, students will be able to model real and noisy data, to retrieve information in very large databases, and to conceive complex systems based on such techniques.
This is a full time program of 2 years divided into four semesters and starting in early October. The first year lectures are taught in English with intensive French courses in parallel, and the first semester contains levelling technical courses. The second year lectures are taught in French, with monitoring and on-line materials both available in English. The fourth semester is devoted to the preparation of a Master thesis in a public or private research centre.
Keywords: Automatic classification, multi-sensor data, signal processing, statistical models, data fusion, computer vision, data analysis, content-based indexing and retrieval, big data, multimedia databases.
This semester is spent performing a Research Project (Master thesis) in an industrial or university R&D laboratory.
You can consult on line, the complet catalog of courses of Telecom SudParis (in French).
In several applicative areas such as telecommunications, medical imaging, virtual reality, telemonitoring, biometrics, bio informatics, environmental sciences, banking, insurance, data mining (textual, multimedia), great amounts of data are captured through specialized sensors and must be processed and further analyzed for different purposes related to the application. Processing such volumes of data, often noisy or degraded, is a big challenge: raw data must be pre-processed to remove the noise, pertinent information (features) must be extracted from the data, which must be stored appropriately and accessed efficiently; this requires to model data in order to label it for classification or prediction purposes.
The high quality lectures and projects supervised by professors from Telecom SudParis and professionals from industry ensure the possibility of applying for a PhD position in a research laboratory, or a research and development position in industry as a data scientist.
Sonia Garcia is Full Professor in the Intermedia (Interaction for Multimedia) Research Team at Telecom SudParis. Her research interests are focused on Pattern Recognition and Machine Learning, Online Handwriting Analysis, Online Signature Verification, Statistical Quality Measures, Health Applications and Biometric Authentication. She has been the coordinator of 3 international competitions on Online Signature Verification and has been actively involved in European projects dealing with Biometrics.
For more information, see http://www-public.tem-tsp.eu/~garcia/
mise à jour le 31/10/2016
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