1. Accueil
  2. EN
  3. Studying at ULB
  4. Find your course
  5. UE
STAT-S502

Data management and analytics

academic year
2023-2024
2024-2025

Course teacher(s)

Pierre DEVILLE (Coordinator)

ECTS credits

5

Language(s) of instruction

english

Course content

  • Relational Databases (Python & SQL)

  • NoSQL Databases (MongoDB)

  • Data Sources and Acquisition

  • Data Security and Privacy

  • Supervised Learning

  • Unsupervised Learning

  • Text Mining

Objectives (and/or specific learning outcomes)

At the end of this course, students will be able to

  • Understand the challenges and limits associated to the Big Data phenomena in a business and economic context

  • Acquire and exploit different types of large-scale data in the context of relational and non relational databases

  • Analyse large-scale data using machine learning, data mining and text mining concepts in order to solve complex problems in business or economics.

Teaching methods and learning activities

36h of Theory and 24h of guided exercices

Contribution to the teaching profile

The course contributes to the development of the following skills of the program profile:

  • Design and exploit large-scale databases in order to extract relevant information through quantitative tools.

  • Ad-hoc identifying appropriate data and getting access to it for empirical analysis

  • Analyse complex problems "out of the box" while respecting rules of experimental and scientific methods in order to design innovative solutions

  • Use of machine learning, data mining and text mining techniques in order to help develop decision, evaluation and prospective tools

  • Demonstrate good summarizing skills to go to the essentials in his communication

References, bibliography, and recommended reading

(1) Elmasri and Navathe. Fundamentals of Database Systems (6th edition), 2011.

(2) Provost, Foster, and Tom Fawcett. Data Science for Business: What you need to know about data mining and data-analytic thinking. " O'Reilly Media, Inc.", 2013.

Other information

Additional information

This unit will also contribute to develop :

  • A quantitave dimension

  • Critical spirit ("esprit critique")

  • Ethics

Contacts

pdeville@ulb.ac.be

Evaluation

Method(s) of evaluation

  • Other

Other

Written exam and group projects

Mark calculation method (including weighting of intermediary marks)

Written exam (70%) + group projects (30%)

Language(s) of evaluation

  • english
  • french

Programmes