BIG DATA OR DATA SCIENCE

Responsible Academic Unit: SCHOOL OF SYSTEMS ENGINEERING
Code: 01403
Number of Credits: 3
Hours: 48
Schedule: MONDAY TO FRIDAY 08:00 – 10:00 AM

Course Description
Data Science is an interdisciplinary area of work that includes processes to collect, prepare, analyze, visualize and model data that allow the generation of useful knowledge to understand complex problems and help in decision making. These data are often unstructured and heterogeneous. On many occasions, these are large volumes of data that, due to their complexity and diversity, require innovative architectures and techniques to extract relevant knowledge: it is the well-known big data. Data Science is an emerging field with high applicability in health sciences, marketing, business, financial markets, transportation, communications, social networks, etc.
As indicated by the consulting firm Gartner (the most prestigious in information technology), data scientists are not traditional business analysts, they are professionals with the rare ability to obtain mathematical models from data that generate clear and convincing business benefits. Thus, professionals with skills in fields such as computer science, mathematics, statistics or business who master new technologies and know how to manage data are increasingly required. Companies in all sectors are increasingly adopting Data Science, so the demand for experts in this sector is enormous; This is reflected in a study by the MIT Sloan Management Review (2015). It is considered one of the best job opportunities in the coming years. Listed by the Harvard Business Review as the 'sexiest profession of the 21st century' (2012). According to a LinkedIn study (2015), the number of Data Science professionals has doubled in the last four years. Another study by Burtch Works (2015) recognizes the positive impact on salary of including Data Science knowledge.

Course Objectives

  • Define business strategies that allow progress in a highly competitive environment
  • Handle databases and queries in parallel
  • Relate the concepts of Big Data and Business Intelligence
  • Model statistics and their pitfalls
  • Differentiate techniques to collect and process information.
  • Detect patterns and predict behaviors

Contact information:

International Relations Office – PBX: (57) 6517013 Ext 3410 – 3411
chiefinternational@unisinucartagena.edu.corelininternationals@unisinucartagena.edu.co
Avenida al Bosque Transversal 54 N° 30 – 453 – Santillana Headquarters – Cartagena de Indias, D. T y C – Bolívar, Colombia.

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