Data Science
Note: this specialization was formerly known as Data Mining and Business Intelligence
About
The master’s degree equips graduates with solid knowledge and hands-on experience in techniques for managing, analyzing and extracting hidden knowledge from structured and unstructured big data ensembles and in building adaptive analytic systems that are able to exploit that knowledge in modern organizations. In particular, the master’s degree addresses the new challenges of the smart society boom: fraud detection, bioinformatics, information extraction from linked open data, real time analysis of sensor data and social networks, and customer relationship management.
Target
The specialization in Data Science is aimed at students from all over the world. Candidates must have a bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or related fields, as well as a good level of English, and they must be motivated to discover knowledge from data in the fascinating world of sciences and technologies.
Specialization coordinator
| Person | Department | |
|---|---|---|
| Romero Moral, Oscar | ESSI |
Specialization teachers
Subjects
Specialization compulsory subjects
- Data Analysis and Knowledge Discovery (DAKD-MIRI)
- Data Warehousing (DW-MIRI)
- Machine Learning (ML-MIRI)
- Multivariate Analysis (MVA-MIRI)
- Open Data (OD-MIRI)
Specialization complementary subjects
- Algorithmics for Data Mining (ADM-MIRI)
- Advanced Human Languages Technologies (AHLT-MAI)
- Advanced Statistical Modelling (ASM-MIRI)
- Big Data Management (BDM-MIRI)
- Bioinformatics and Statistical Genetics (BSG-MIRI)
- Information Retrieval (IR-MIRI)
- Kernel-Based Machine Learning and Multivariate Modelling (KMLMM-MIRI)
- Optimization Techniques for Data Mining (OTDM-MIRI)
- Statistical Natural Language Processing (SNLP-MIRI)
- Service Oriented Business Intelligence (SOBI-MIRI)
Elective
Mandatory
Final Master Thesis
Mandatory Common Course
Semester 1
Algorithmic Methods for Mathematical Models
(AMMM - 6 ECTS)
(AMMM - 6 ECTS)
Data Analysis & Knowledge Discovery
(DAKD - 6 ECTS)
(DAKD - 6 ECTS)
Data Warehousing
(DW - 6 ECTS)
(DW - 6 ECTS)
Statistical Modelling and Design of Experiments
(SMDE - 6 ECTS)
(SMDE - 6 ECTS)
Techniques and Methodology of Innovation and Research in Informatics
(TMIRI - 6 ECTS)
(TMIRI - 6 ECTS)
Semester 2
Concurrence, Parallelism and Distributes Systems
(CPDS - 6 ECTS)
(CPDS - 6 ECTS)
Machine Learning
(ML - 6 ECTS)
(ML - 6 ECTS)
Multivariate Analysis
(MVA - 6 ECTS)
(MVA - 6 ECTS)
Open Data
(OD - 6 ECTS)
(OD - 6 ECTS)
Semester 3
Semester 4
Final Master Thesis
(TFM - 30 ECTS)
(TFM - 30 ECTS)
Seminar activities
The activities to obtain the SIRI credits can be done in any semester of the master's degree. Consult the detail of the seminars.
Seminars of Innovation and Research in Informatics
(SIRI - 6 ECTS)
(SIRI - 6 ECTS)
Specialization Elective
Algorithmics for Data Mining
(ADM - 6 ECTS)
(ADM - 6 ECTS)
Advanced Human Language Technologies
(AHLT - 5 ECTS)
(AHLT - 5 ECTS)
Advanced Statistical Modelling
(ASM - 6 ECTS)
(ASM - 6 ECTS)
Big Data Management
(BDM - 6 ECTS)
(BDM - 6 ECTS)
Bioinformatics and Statistical Genetics
(BSG - 6 ECTS)
(BSG - 6 ECTS)
Information Retrieval
(IR - 6 ECTS)
(IR - 6 ECTS)
Kernel based Machine Learning and Multivariate Modelling
(KMLMM - 6 ECTS)
(KMLMM - 6 ECTS)
Optimization Techniques for Data Mining
(OTDM - 6 ECTS)
(OTDM - 6 ECTS)
Elective
It is also possible:
- Recognize credits for "External Practices" or "Laboral and Professional Experience"
- Take courses from other MIRI specialties
- Take courses from other masters at the UPC
Where we are
B6 Building Campus Nord
C/Jordi Girona Salgado,1-3
08034 BARCELONA Spain
Tel: (+34) 93 401 70 00
C/Jordi Girona Salgado,1-3
08034 BARCELONA Spain
Tel: (+34) 93 401 70 00
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