Objectives and competences

The main goal of the Data Science Course: Applications in Biology and Medicine with Python and R is to provide a solid introduction to the field of data science and to explore the most advanced statistical and computational techniques so that you can become a data scientist. The core function of a data scientist is to extract information from complex datasets that may be useful for research in biological sciences (biology, biotechnology, biochemistry, etc.) and in medicine, and for business decision-making.
The course gives you the tools and resources you need to become a data scientist.

Basic information

TypePostgraduate courses
CertificateAdvanced university course
Faculty or schoolFacultat de Biologia
Branch of knowledge
  • Biology and genetics
  • Pharmacy
  • Medicine and dentistry
Mode of deliveryDistance
Credits9
Length of course1 academic year
Language(s) of instructionEnglish
Enrolment fee:First year: 750,00 €
An increase of 10% is applied to the price, up to a maximum of € 70, as administration fee
In-company placement(s):No
Classes begin:03/04/2024
E-mailamonleong@ub.edu
Master's degree course homepage https://www.researchgate.net/profile/Antonio_Monleon-Getino
ManagmentMonleón Getino, Antonio
Open pre-enrolmentNo
Lead to doctoral studiesNo
Admission for applicants not holding a degree qualification:Sí, amb crèdits pendents (10% o menys)

Objectives and competences

Objectives

- To learn the basics of data science and study the most advanced statistical and computational techniques to become a data scientist.
- The core function of a data scientist is to extract information from complex datasets that may be useful for research in biological sciences (biology, biotechnology, biochemistry, etc.) and in medicine, and for business decision-making. As science goes into the digital age and continues to join the broader technology industry, the scope of data science needs is increasingly wide.

Data scientists in this emerging space are regularly in charge of dealing with sophisticated problems, such as reducing the burden of repetitive tasks on biologists, biotechnologists, biochemists or doctors; developing platforms for high-performance genomic analysis; identifying new molecular targets for drug discovery; optimizing clinical trial procedures; analysing digital medical data to improve patient care and prevent the progression of a disease, to reduce mortality rates.

Due to the rapid development of biomedical research, bio-scientists have shown the need to adopt concepts and tools from other areas, such as automatic learning, computational chemistry, engineering, mathematics, physics or biodiversity. The paradigm shift drives many initiatives in the field of life, health and information; among others, precision medicine, value-based healthcare, genomics or biomonitoring. On the other hand, the differences in the industry of life, health and technology tend to favour data scientists who understand the domain and its implicit challenges.

Access and admission

Applicant profile and access requirements

Recommended applicant profile

Bioscience and medical professionals (biologists, doctors, biotechnologists, biochemists, pharmacists, bioengineers, etc.).

Access requirements:
- An intermediate understanding of statistics, mathematics and computer science (similar to that required in study programmes in the sciences, in medicine, etc.).
- Basic programming knowledge (R, Python, etc.).
- Intermediate proficiency in English (Cambridge level B)
- To take the course, students must bring a laptop computer to class, preferably one that uses a Windows or Linux operating system.

Access requirements and conditions

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.

Pre-enrolment

Contact us

Faculty or school where the course is taught


Address:IL3 - Universitat de Barcelona
C/ Ciutat de Granada

08018 - Barcelona
Espanya
Email address:amonleong@ub.edu
Webpage:
Telephone:34 93 403 96 96
Observations:Remote classroom of IL3-UB, Mondays and Wednesdays from 4 to 8 pm.

For further enquiries


Address:Antonio Monleón Getino
Secció Estadística. Departament Genètia, Microbio
i Estadística. Fac Biologia. Avda Diagonal 643
08028 - Barcelona
Espanya
Email address:amonleong@ub.edu
Webpage:https://www.researchgate.net/profile/Antonio_Monleon-Getino
Telephone:678329864
Observations:see the previous field.