University Carlos III of Madrid
Bachelor’s Degree in Data Science and Engineering (English)
Leganés, Spain
DURATION
4 Years
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
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EARLIEST START DATE
Sep 2024
TUITION FEES
EUR 7,000 / per year *
STUDY FORMAT
On-Campus
* for international students | for EU students: € 1,500/year
Scholarships
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Introduction
The world of the 21st century generates massive amounts of data and, therefore, urgently needs experts capable of extracting meaning from them and putting them into value.
The Degree in Science and Data Engineering will train professionals with the ability to analyze, both theoretically and practically, said data for intelligent decision-making. If you are a person with analytical skills, critical thinking, computer skills, and mathematical skills, this degree will prepare you to generate practical solutions to technological, business, and social problems.
Combine the study of fundamental subjects such as mathematics or computer science, with the new tools coming from the digital technologies of information and communication, including statistics, artificial intelligence, or machine learning. In short, the Degree will turn you into a leader of the fourth industrial revolution.
Studies in English only
This degree courses completely in English. No groups are available in Spanish in any subject. You must take into mind that:
- In groups in English, all work (classes, drills, exercises, tests, etc.) shall be conducted in English.
- During the first year, it must establish an English B2 level, pass a test, and provide one of the supported official certificates or any way determined by the university.
- After completing the studies, the DS mention of having carried out the studies in English will appear.
Employability and professional internships
UC3M has agreements with over 3000 companies and institutions in which students can undertake internships and access job openings.
A total of 93.4 % of graduates from this University enter the job market the first year after finishing their studies, according to the 2019
Admissions
Curriculum
Year 1 - Semester 1
- Calculus I (6 credits)
- Introduction to Data Science (6 credits)
- Linear algebra (6 credits)
- Probability and Data Analysis (6 credits)
- Programming (6 credits)
Year 1 - Semester 2
- Advanced knowledge of Spreadsheets (1,5 credits)
- Calculus II (6 credits)
- Computer Networks (6 credits)
- Data structures and algorithms (6 credits)
- Information skills (1,5 credits)
- Introduction to Statistical Modeling (6 credits)
- Writing and communication skills (3 credits)
Year 2 - Semester 1
- Automata theory and compilers (6 credits)
- Data Base (6 credits)
- Discrete mathematics (6 credits)
- Signals and Systems (6 credits)
- Statistical Learning (6 credits)
Year 2 - Semester 2
- Data protection & cybersecurity (6 credits)
- Machine Learning I (6 credits)
- Numerical methods (6 credits)
- Predictive Modeling (6 credits)
- Statistical Signal Processing (6 credits)
Year 3 - Semester 1
- Introduction to business (6 credits)
- Machine Learning II (6 credits)
- Massive computing (6 credits)
- Optimization and Analytics (6 credits)
- Web Applications (6 credits)
Year 3 - Semester 2
- Bayesian Data Analysis (6 credits)
- Data engineering legal and ethical issues (3 credits)
- Machine learning applications (6 credits)
- Mobile Applications (6 credits)
- Neural Networks (6 credits)
- Soft Skills (3 credits)
Year 4 - Semester 1
- Audio processing, Video processing, and Computer vision (6 credits)
- Data Science Project (6 credits)
- Web Analytics (6 credits)
Electives: Recommended 12 credits
Year 4 - Semester 2
- Humanities (6 ECTS)
- Bachelor Thesis (12 ECTS)
Electives to choose in 4th year - First semester
At the end of your studies, you should have earned a total of 18 elective credits of the Bachelor in Data Science and Engineering.
- Cybersecurity Engineering (6 ECTS)
- Functional data analysis (6 ECTS)
- Fundamentals of BioInformatics (6 ECTS)
- Internet Networking Technologies for Big Data (6 ECTS)
- Machine Learning in Healthcare (6 ECTS)
- Professional Internships (18 ECTS)
- Regression in High Dimension (6 ECTS)
- Simulation and Resampling methods (6 ECTS)
Electives to choose in 4th year - Second semester
At the end of your studies, you should have earned a total of 18 elective credits of the Bachelor in Data Science and Engineering.
- Artificial Intelligence (6 ECTS)
- Data Design for Sensemaking (6 ECTS)
- Educational data analytics (6 ECTS)
- Inference methods in Bayesian Machine Learning (6 ECTS)
- Professional Internships (18 ECTS)
- Robotics (6 ECTS)
- Stochastic Dynamical Systems (6 ECTS)
- Time Series and Forecasting (6 ECTS)
- Advanced Internet Networking Technologies (6 ECTS)
Mobility
Exchange programs
The Erasmus program permits UC3M first-degree and postgraduate students to spend one or several terms at one of the European universities with which UC3M has special agreements or take up an Erasmus Placement, a work placement, or an internship at an EU company. These exchanges are funded with Erasmus Grants which are provided by the EU and the Spanish Ministry of Education.
The non-European mobility program enables UC3M degree students to study one or several terms in one of the international universities with which the university has special agreements. It also has funding from the Banco Santander and the UC3M.
These places are offered in a public competition and are awarded to students with the best academic record and who have passed the language threshold (English, French, German, etc..) requested by the university of destination.
Rankings
- QS World University Rankings Top 50 Under 50
- 35th spot worldwide and ranked 10th in Europe, on QS Top 50 Under 50 Ranking
- QS World University Rankings
- 319th position on the QS World University Rankings 2024
- QS World University Rankings Subjects Rankings
- Among the world’s best universities in 13 academic fields, according to QS World University Rankings by Subject 2023
- QS Graduate Employability Rankings
- Among the 136 best universities in the world for employability, according to THE’s Global University Employability Ranking 2022
Program Outcome
Graduates with a Bachelor's Degree in Data Science and Engineering must be able to design and manage infrastructures that support large amounts of data for subsequent analysis, to design and build systems capable of integrating data from various sources and process large volumes of data to optimize the performance of the data ecosystem of a company, organization or entity. In addition, graduates will be able to convert raw data into knowledge, applying statistical, machine learning, and pattern recognition techniques to solve critical business problems.
To this end, graduates will have strong programming skills, the ability to design new algorithms, handle large volumes of data, and the analytical skills to interpret the results of their findings and display them using visualization techniques. Graduates will also need to be up to date with the latest cutting-edge computing technologies, as they will have to work with datasets of different natures and be able to run their algorithms on big data effectively and efficiently.
Furthermore, they will be able to develop their professional career in all industrial and professional sectors that demand the profile of a data scientist and data engineer.
The work of the data scientist is closely related to business strategy in a wide variety of sectors, as machine learning and artificial intelligence technologies find application at various business levels, ranging from business intelligence itself to human resources, to customer and supplier management or digital marketing.
Program Tuition Fee
Career Opportunities
The work of the data scientist is closely related to business strategy in a wide variety of sectors, as machine learning and artificial intelligence technologies find application at very different levels, ranging from business intelligence itself to human resources selection, to customer and supplier management or digital marketing.
In particular, we highlight certain strategic sectors in which artificial intelligence is expected to have a strong impact: high technology and communications, media and entertainment, automotive and assembly, basic resources and services, transportation and logistics, healthcare, biosciences, professional services, retail, education, marketing, customer and supplier relations, and the public sector.
As a consequence of the above, there is a wide range of job possibilities for the data scientist and data engineer, among which we can cite, for example:
- Data Scientist (generalist denomination that encompasses data management, design, and development of artificial intelligence algorithms in any sector).
- Data Engineer (generalist designation that provides hardware and software support to Data Science)
- Software Developer (software engineering in the field of artificial intelligence)
- Web/mobile application developer (data capture, storage, management, and visualization)
- Intelligent services designer and developer
- Strategy Engineer (alignment of the organization's strategy with the required technology)
- Data Analytics Manager
- Director of Digital Research and Development
- Digital business leader and strategist
- Digital Business Development Manager
- Director of Digital Innovation, Digital Product
- Digital Marketing Director
- Digital Business Consultant
- Executive Director
- Digital Transformation Director
- Digital Sales Director
- Digital Operations Director