Objectives and competences
The master's degree in Big Data and Data Science has a totally practical approach to respond to the need of companies to incorporate specialized professionals. The course gives participants the skills they need to learn how to use and implement the major tools required for data science, such as Hadoop and Spark, various NoSQL and SQL databases and tools for the implementation of machine learning, neural networks and deep learning, in addition to cloud tools (laaS, PaaS, SaaS, Google, Azure, AWS, etc.) and tools for control (Github, etc.) and and analysis (programming in R and Python).
Basic information
| Type | Postgraduate courses |
|---|---|
| Certificate | Lifelong learning master's degree certificate |
| Faculty or school | Institut de Formació Contínua IL3 |
| Branch of knowledge |
|
| Mode of delivery | Distance |
| Credits | 60 |
| Length of course | 1 academic year |
| Language(s) of instruction | Spanish |
| Enrolment fee: | First year: 6.250,00 € An increase of 10% is applied to the price, up to a maximum of € 70, as administration fee |
| In-company placement(s): | No |
| Start of teaching period: | 18/03/2025 |
| End of teaching period: | 16/03/2026 |
| info@il3.ub.edu | |
| Master's degree course homepage | https://www.il3.ub.edu/ca/master-big-data-science |
| Managment | Lorente Muñoz, Dolores |
| Open pre-enrolment | No |
| Lead to doctoral studies | No |
| Admission for applicants not holding a degree qualification: | Sí, amb crèdits pendents (10% o menys) |
Objectives and competences
Objectives
- To gain broad knowledge of the display of data and digital data.
- To be able to extract relevant information for the company through the application of data science techniques and learn to carry out efficient web scraping.
- To learn to develop algorithms for neural networks, deep learning and advanced machine learning.
- To acquire an advanced understanding of programming in R and Python.
- To work and develop projects in SQL, MongoDB, Spark and Hadoop.
- To improve in the efficient use of time with methodologies such as Agile or Scrum.
Access and admission
Applicant profile and access requirements
Recommended applicant profile
Preferably, students with technical profiles who are interested in developing their professional career in the field of analysis and management of large volumes of data.Admission requirements:
- Engineers or bachelor's degree holders in Computer Science, Telecommunications or Industrial Technologies.
- Bachelors/graduates in mathematics, physics, chemistry and statistics are given priority.
Access for students without a university degree who have been working in the areas of business intelligence, business analytics, etc. for at least two years may be considered. In this sense, they can access the course if they fit into one of these technical profiles:
- People with knowledge of analysing and managing data or at least two years of work experience in analytical departments.
- People with knowledge of programming (preferably SQL, Python or R) or who have programmed for at least two years in a company.
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: | Institut de Formació Contínua - UB C/ Ciutat de Granada, 131 08018 - Barcelona Espanya |
|---|---|
| Email address: | info@il3.ub.edu |
| Webpage: | http://www.il3.ub.edu |
| Telephone: | 93 403 96 96 |
| Observations: | Online learning |
For further enquiries
| Address: | Institut de Formació Contínua - UB C/ Ciutat de Granada, 131 08018 - Barcelona Espanya |
|---|---|
| Email address: | info@il3.ub.edu |
| Webpage: | https://www.il3.ub.edu/ca/master-big-data-science |
| Telephone: | 93 403 96 96 |
| Observations: | Monday to Friday, from 9 a.m. to 7 p.m. |