Studyportals

Data Mining and Knowledge Management

Sorbonne University

Master On Campus
24 months
Duration
8000 EUR/year
4000 EUR/year
Unknown
Tuition fee
Unknown
Unknown
Apply date
Unknown
Unknown
Start date

About

Data mining and knowledge management (DMKM) has become essential for improving the competitiveness of businesses and increasing access to knowledge. DMKM still, however, comes up against major scientific and technological obstacles. This EMMC’s degree in DMKM proposes specialist training in this field.

Overview

The sheer amount of numerical data, textual documents, images, video, Web sites available today is overwhelming, and cannot satisfy, per se, the emerging knowledge society. It is indeed necessary to extract, from this wealth of information, the knowledge hidden inside. Only this ability could guarantee a better future to the individuals and the society, as well as a sustainable economical development and competitiveness.

To locate useful information, to transform it into actionable knowledge, and to manage its use for decision-making can be accomplished through the exploitation of methodologies and tools of Data Mining and Knowledge Management (DMKM). Notwithstanding the availability on the market and in academic environments of advanced solutions and systems, DMKM still calls for further research and developments to face new important challenges. In particular, some hot issues are still to be tackled, such as the following ones:

  • To face the exponential increase of data it is not sufficient to rely on larger storing devices and/or faster computers. New intelligent approaches are to be designed to tame the very size of data.
  • Data assume different modalities, such as numbers, texts, audio-video, sensor signals, and so on. Integrating into a unique system such complex data is still a challenge. Also, spatial distribution of data (for instance, on several Web sites or different data bases) is a source of difficulty for integration.

Competences and skills

  • At the end of the programme, the successful students shall have acquired competences in computer science, applied mathematics and statistics, and advanced information processing methods that will allow them to:
  • Perform in-depth analysis of information requirements for solving problems;
  • Manage large databases;
  • Make use of such databases with the goal of extracting from them hidden information and knowledge;
  • Deploy this knowledge in decision support systems or intelligent systems, both in academic and in industrial environments.
  • Around 50% of the programme is devoted to applications in the field, solving real data mining problems and the implementation of the standard techniques liable to be encountered by students in their future professional activities.

Programme Structure

Common courses. These are composed of 10 courses: 6 in Semester 1, 2 in Semester 2 and 2 in Semester 3. They are devoted to providing the students with the theoretical and methodological background for the specialties. 

All common courses will be guaranteed to be multi-localized by the partner universities, through video-conferencing. One teacher or a team can give each course. The courses will be then available to all students independently from the country they live in. In this way, all students will share a common background (same pedagogical content, same teachers and same language with a virtual unity of place). To every course teachers available locally at each university will supply 15 additional hours of tutoring.

Key information

Duration

  • Full-time
    • 24 months

Start dates & application deadlines

We did our best, but couldn't find the next application deadline and start date information online.

Language

English

Credits

120 ECTS

Delivered

On Campus

Academic requirements

We are not aware of any academic requirements for this programme.

English requirements

TOEFL admission requirements TOEFL® IBT The TOEFL iBT® is given online through the internet at designated testing site. The test measures your English-language abilities in an academic setting. The score refers to the total score of 4 subjects (writing, listening, speaking, and reading), each subject has a range of 0 - 30.
80
IELTS admission requirements IELTS The International English Language Test System (IELTS) tests your English-language proficiency on a scale of 1 – 9. The score refers to the combined average score of 4 subjects (writing, listening, speaking, and reading).
6

Other requirements

General requirements

  • Be the holder of a Bachelor degree (a minimum of three years' study at a university and corresponding to the equivalent of 180 ECTS) in the fields of Computer Science, Mathematics or Statistics.
  • Mastering English at a level equivalent to 550 TOEFL.
  • In the following table the conversion among different English evaluation systems is reported. The minimum accepted for the European Master DMKM is “TOEFL Paper 550” or equivalent.

Tuition Fee

  • International

    8000 EUR/year
    Tuition Fee
    Based on the original amount of 8000 EUR per year and a duration of 24 months.
  • EU/EEA

    4000 EUR/year
    Tuition Fee
    Based on the original amount of 4000 EUR per year and a duration of 24 months.

Funding

Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.

Fresh content

Updated in the last 9 months

Check the official programme website for potential updates.

Our partners

Data Mining and Knowledge Management
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Sorbonne University

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