Bachelor in Data Science
Programme
- Undergraduate
Delivery mode
- Face-to-face
Language
- Spanish
Credits
- 240 ECTS
Bachelor in Data Science
The Bachelor in Data Science trains scientists capable of mining and handling massive amounts of information during every stage of the process. Students acquire the necessary knowledge and skills to design data searches, selecting specific data sources and variables of interest according to each problem or project. They also learn to process data using denoising, outlier detection and normalisation methods, and to propose hypotheses, provide answers and solve any prediction, planning and prevention issues that may arise during projects.
The curriculum addresses fundamental aspects of statistics, mathematics, databases, and programming. It also covers other areas that are essential for data scientists, including automatic learning techniques, such as Machine Learning or Deep Learning, or cloud technologies, such as Big Data, Cloud Services and Cloud Computing.
A gateway
to a new future
Curriculum
CUNEF Universidad’s Bachelor in Data Science consists of 240 ECTS, distributed as follows:
- 60 basic ECTS
- 162 compulsory ECTS
- 12 ECTS for elective courses or internships
- 6 ECTS for the Final Degree Project (FDP)
Fall Term
| COURSE | ECTS | TYPE |
|---|---|---|
| Linear Algebra | 6 | Basic |
| Descriptive Statistics | 6 | Basic |
| Programming for Data Science I: R | 6 | Basic |
| Mathematical Logic | 6 | Basic |
| Search, Processing and Use of Information | 6 | Compulsory |
| TOTAL CREDITS FALL TERM | 30 |
Spring Term
| COURSE | ECTS | TYPE |
|---|---|---|
| Calculus I | 6 | Basic |
| Probability Calculus | 6 | Basic |
| Programming for Data Science II: Python | 6 | Basic |
| Algorithm Analysis and Design | 6 | Basic |
| Critical Thinking and Argumentation | 3 | Compulsory |
| Verbal and Written Communication Skills | 3 | Compulsory |
| TOTAL CREDITS SPRING TERM | 30 |
Fall Term
| COURSE | ECTS | TYPE |
|---|---|---|
| Calculus II | 6 | Basic |
| Discrete Mathematics | 6 | Compulsory |
| Inferential Statistics | 6 | Compulsory |
| Databases I (SQL Relational Model) | 6 | Basic |
| Cloud Storage | 6 | Compulsory |
| TOTAL CREDITS FALL TERM | 30 |
Spring Term
| COURSE | ECTS | TYPE |
|---|---|---|
| Web Application Programming | 6 | Compulsory |
| Time series | 6 | Compulsory |
| Machine Learning: Prediction | 6 | Compulsory |
| Databases II (NoSQL Model) | 6 | Compulsory |
| Cloud Computing | 6 | Compulsory |
| TOTAL CREDITS SPRING TERM | 30 |
Fall Term
| COURSE | ECTS | TYPE |
|---|---|---|
| Collaboration Tools | 6 | Compulsory |
| Operational Research | 6 | Compulsory |
| Geometry and Spatial Data | 6 | Compulsory |
| Machine Learning: Classification | 6 | Compulsory |
| Evolution of Natural and Artificial Intelligence | 6 | Compulsory |
| TOTAL CREDITS FALL TERM | 30 |
Spring Term
| COURSE | ECTS | TYPE |
|---|---|---|
| Visualisation Techniques | 6 | Compulsory |
| Agile Project Management | 6 | Compulsory |
| Optimisation | 6 | Compulsory |
| Corporate Data Ecosystems | 6 | Compulsory |
| Deep Learning | 6 | Compulsory |
| TOTAL CREDITS SPRING TERM | 30 |
Fall Term
| COURSE | ECTS | TYPE |
|---|---|---|
| Data Protection and Privacy | 6 | Compulsory |
| Processing Economic and Financial Data | 6 | Compulsory |
| Data-Driven Logistics | 6 | Compulsory |
| Natural Language Processing for Marketing | 6 | Compulsory |
| Data-Driven Financial Risk Assessment | 6 | Compulsory |
| TOTAL CREDITS FALL TERM | 30 |
Spring Term
| COURSE | ECTS | TYPE |
|---|---|---|
| Business Intelligence | 6 | Compulsory |
| Decision-Making Tools | 6 | Compulsory |
| Internships or Elective Courses | 12 | Elective |
| Final Degree Project | 6 | Compulsory |
| TOTAL CREDITS SPRING TERM | 30 |
Career Outcomes
Data Science graduates are in high demand and have a wide range of businesses to choose from when they enter the job market. Their skillset has become essential for almost any type of business, especially in areas such as finance, marketing, healthcare and the environment. The research study “Forecast: Enterprise Software Markets Worldwide, 2014-2021”, recently published by the consulting firm Gartner, shows that the global data market is growing dramatically and identifies data science as “the profession of the future”.