GENERAL INFORMATION
  • Name of course :
    INTRODUCTION TO DATA SCIENCE AND MACHINE LEARNING
  • Qualification awarded:
    Curs Superior Universitari (Degree Universitat Barcelona)
  • Number of credits:
    12,00
  • Centre responsible :
    Faculty of Mathematics and Computer Science
  • Length of course (in academic years):
    1
  • Mode of delivery (face-to-face/ blended/ distance):
    Distance
MANAGEMENT:

  • Seguí Mesquida, Santi

  • Vitrià Marca, Jordi

RECOMMENDED APPLICANT PROFILES AND ADMISSION REQUIREMENTS:

- University graduates in computing, statistics and mathematics, interested in learning about the world of data science.
- Holders of other qualifications who have basic notions of data processing, statistics and computer science.

Access requirements:
- Acquire a basic level of programming skills in Python, because the course is practical and very much oriented to the use of computer techniques to solve specific cases.
- Students should also have their own laptop, to be able to work through the interactive lessons.

ADMISSION FOR APPLICANTS NOT HOLDING A DEGREE QUALIFICATION:

The course is also open to students with no prior university education, who will acquire the same knowledge and skills and receive a specific qualification for their learner group. Information on the access requirements and other conditions can be obtained from the course directors.

LEARNING OBJECTIVES:

- Be aware of the new social challenge associated with the use of computers and electronic devices in daily life and in many habitual activities and learn to give meaning to the large volumes of data that are generated every day and take advantage of them.
- To gain knowledge of data science, a new professional area to respond to the technological and social challenge of controlling and interpreting the vast amount of data that are generated on actions that take place in the real world in many aspects of personal and professional life, from electronic purchases to scientific or financial research, given that these data are just noise if they are not monitored and interpreted.
- To gain a sound understanding of computing, statistics and mathematics, which are at the core of big data, a key element in areas such as genetics (for example, to decode the human genome), personalised health, internet information, interactions in social networks and even applied physics or astronomy. To learn about the most suitable technological environments for development, given that a key aspect of data science is the need to process very large datasets that exceed the capacity of current computers.
- The course is based on an ecosystem of tools, focused on Python language, which covers all phases of a big data project: from data exploration and prototyping to data-based product development.

FURTHER INFORMATION OF INTEREST
  • Enrolment fee:
    • 1.850,00 €
    • An increase of 10% is applied to the price, up to a maximum of € 70, as administration fee
  • In-company placement(s):
    No
  • Date on which pre-enrolment begins:
    6/1/2021
  • Date on which pre-enrolment ends:
    7/30/2021
  • Classes begin:
    10/1/2021
FACULTY OR SCHOOL WHERE THE COURSE IS TAUGHT
  • Name of individual or institution:
    Virtual - Facultat Matemàtques i Informàtica
  • Address:
    Virtual - Gran Via de les Corts Catalanes 585
    08006 Barcelona
    Espanya
  • Email address:
    datascience@ub.edu
  • Webpage:
    http://www.ub.edu/datascience/
  • Telephone:
    93 402 15 97
  • Observations:
    Online
FOR FURTHER ENQUIRIES