The digital revolution that emerges from Big Data implies exciting challenges and opportunities for companies and organizations. Consequently, the labor market demands more and more specialized professionals in this field.
The Executive Master in Big Data Science (MEBDS) was born as a response to this new reality: it offers a technical program and, at the same time, very practical: it has a multidisciplinary faculty of professors and academics from the Universidad de Navarra , experts in the Big Data area of large multinational companies of high prestige. The purpose is to seek the scientific rigor proper to the University, enriching it with the experience of professionals and real business cases in various fields.
The Executive format of the title, with face-to-face sessions on Friday afternoons and Saturday mornings, makes it easier to combine professional performance with class attendance, and to promote networking among professionals and companies.
The MEBDS is coordinated by the Data Science Unit of the Culture and Society Institute, the Humanities and Social Sciences research center of the Universidad de Navarra .
The Executive Master in Big Data Science seeks to bring business statistics closer to the technological reality of companies, providing professionals with tools to collect, prepare, analyze and interpret and present results. In addition, students will be able to lead the implementation of novel Big Data projects in real environments, applying the concepts to the business sector of interest.
Although the MEBDS is not designed for senior executives, it is expected that in their professional future they will end up being once it is well known what a company needs to benefit from the information it can potentially generate. Therefore, at the end of the program you will be able to know well what requirements a person must have to be integrated into your team, until they know precisely the instruments or training that each one should acquire.
Whether your goal is to grow professionally, start and create your own company, or redirect your career, this Master will answer your motivations.
"For all the decisions you make within a company, you need the data. I learned how useful information is and how to use it "
- Gabriela García, Hewlett Packard
The academic plan is divided into four blocks.
1. Data analysis
Traditional statistical methods such as regression models, decision trees or reduction of dimensionality, of proven application in practically all fields, where the student is able to recognize a problem, verify the hypothesis, propose, carry out, validate and interpret a statistical model to solve it.
We also study more recent and novel methodologies more related to machine learning. Among others, RandomForest, K-Means and neural networks are studied.
2. Programming and computing
Starting from a basic level, it is intended that the student acquire intermediate-advanced knowledge and be able to follow the other subjects, as well as develop a certain autonomy for the personal learning phase that precedes the master. The programming languages taught are R and Python, being the most popular and demanded in the professional field.
This block includes the data extraction phase, where the student acquires the training to cope with traditional databases, which are currently the most common in companies. It also includes the management of properly understood environments such as Big Data, such as Hadoop or Spark, and data collection techniques on social networks such as Twitter or Facebook, web scribing or image collection.
Finally, the visualization techniques will be approached with the most demanded tools currently by the business environment.
The Master aims to give a solid formation in terms of technical knowledge, but also seeks to provide a business vision and verbal transmission, so that the graduate can become a bridge between the executive layer and the technical layer in a project. Throughout the sessions students will be shown how to use the techniques learned in real situations and apply them in different sectors.
This section includes Workshops with companies , which will involve professionals from prestigious companies and institutions, with extensive experience in the field. In their sessions they will present real cases of use, as well as practical examples.
The objective is to bring the technological reality closer to the students so that they know first-hand what is being done in the most leading and prestigious international companies.
4. Final Master's Project, TFM
It has a prominent weight in the program. Being co-directed by the Universidad de Navarra as well as by business professionals, it is an excellent opportunity for the student to lead the implementation of impact projects in their professional environment.
To apply for admission , it is necessary that the candidate perform the following steps:
· Online registration in miUNAV, through the web.
· Completion of the application form for admission, attaching the academic and identity documentation of the student that is being scanned.
· A payment of 100 euros must be made as a processing fee.
Forms of payment of processing expenses:
· Via Internet, through the miUNAV portal.
· By bank transfer to the account indicated below. The proof of payment must be attached together with the rest of the documentation through the miUNAV portal and must include the full name of the applicant and the word "ADMISSION".
- Once the application for admission is received, the Executive Master's Big Data Board evaluates and issues the final report on admission. The Admission Service of the University communicates the resolution of the application for admission.
The Universidad de Navarra is ranked number 1 in Spain and 61 in the world in the ranking of employability QS 2019
" The positions related to Data Science and Big Data are the most difficult to cover in Spanish companies "
Study of Professional Profiles and Competencies Most Demanded by the Company - EpyCE, 2018
The professions related to Big Data have the highest labor insertion rates in the international labor market. Some of the professional outcomes of this Master are:
- Data Scientist
- Data Analyst
- Big Data Consultant
- Chief Data Officer (CDO)
- Machine Learning Engineer
- Natural Language Processing Engineer
- Computer Vision Engineer
- Big Data Developer
- Big Data Architect
- Big Data Engineer
- Business Analyst
- Business Intelligence Consultant