Master in Data Science and Business Analytics
Turn data into business decisions. Build practical skills in Python, machine learning, business intelligence and big data through an on-campus master taught entirely in English in Madrid.
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On-Campus
1 Academic Year
English
October and March
Master in Data Science and Business Analytics
Objectives of the Program
The Master in Data Science and Business Analytics develops the technical and analytical skills needed to collect, manage, analyse and model data, and translate the results into business value. It connects programming, statistics and databases with the tools used to understand performance, identify opportunities and support informed decisions.
Across one academic year, students progress from Python and data management to predictive modelling, machine learning, deep learning and big data. The programme combines business intelligence and visual communication with the challenge of turning analytical models into practical business solutions. A two-part Master’s Thesis brings these skills together in an applied project.
- 1 Academic Year
- Madrid
- 60 ECTS
- On-site
- English
- October and March
What you will learn?
- Prepare, explore and analyse data using Python and statistical methods.
- Work with SQL and NoSQL databases to organise and access information.
- Build dashboards and visualisations that communicate useful business insights.
- Develop and evaluate predictive models using machine learning and deep learning.
- Analyse text, social networks and open data to address analytical questions.
- Work with big data technologies and Apache Spark, and connect models to business use cases.
Learning through practice
Learn through practical exercises, real datasets and applied projects, supported by academic staff and professionals from data, analytics and technology. The programme connects technical methods with business questions, helping students explain their findings and develop solutions with a clear purpose.
Tools and technologies
Work with tools and technologies covered in the programme, including Python, Pandas, SQL, MongoDB, Power BI, Tableau, scikit-learn, TensorFlow, Keras, Apache Spark, Hadoop, Git, APIs and cloud environments.
Study Plan
Study Plan: Bachelor in Business Administration
| Python Fundamentals | 3,0 |
| Advanced Python | 3,0 |
| Statistics for Data Science | 3,0 |
| SQL Databases | 3,0 |
| NoSQL Databases | 3,0 |
| Business Intelligence | 3,0 |
| Advanced Data Visualization | 3,0 |
| Open Data | 3,0 |
| Master's Thesis I | 6,0 |
TOTAL FIRST SEMESTER: 30 ECTS
| Data Mining and Predictive Modelling | 3,0 |
| Machine Learning | 3,0 |
| Deep Learning | 3,0 |
| Text Mining | 3,0 |
| Big Data Technologies | 3,0 |
| Apache Spark | 3,0 |
| Social Network Analysis | 3,0 |
| Productizing Models: from Model to Business | 3,0 |
| Master's Thesis II | 6,0 |
TOTAL SECOND SEMESTER: 30 ECTS
| Subject | ECTS |
|---|---|
| Python Fundamentals | 3,0 |
| Advanced Python | 3,0 |
| Statistics for Data Science | 3,0 |
| SQL Databases | 3,0 |
| NoSQL Databases | 3,0 |
| Business Intelligence | 3,0 |
| Advanced Data Visualization | 3,0 |
| Open Data | 3,0 |
| Master’s Thesis I | 6,0 |
| Subject | ECTS |
|---|---|
| Data Mining and Predictive Modelling | 3,0 |
| Machine Learning | 3,0 |
| Deep Learning | 3,0 |
| Text Mining | 3,0 |
| Big Data Technologies | 3,0 |
| Apache Spark | 3,0 |
| Social Network Analysis | 3,0 |
| Productizing Models: from Model to Business | 3,0 |
| Master’s Thesis II | 6,0 |
Professional Opportunities
Career paths depend on each student’s prior experience and area of specialisation.
- Consulting
- Banking and insurance
- Technology
- Retail
- Telecommunications
- Energy
- Public Organisations
Academic Partner
Our Institution
CEDEU University Center is one of the entities linked to the Foundation for Training and Future, founded in 1958. It has more than 40.000 students of 50 different nationalities.
At CEDEU we base our work on innovation, social transformation, the promotion of entrepreneurship and the empowerment of talent as vital pillars of our institution.
Studying at CEDEU is to experience a prestigious education, where we train people with leadership, entrepreneurial spirit , with a creative spirit, social commitment and ethical responsibility as experts in the development of their professional future.
Partner Companies
Areas of the Master
Data foundations and business intelligence
Build a foundation in Python, statistics and SQL and NoSQL databases. Learn to explore information, develop business intelligence outputs and communicate findings through advanced data visualisation and open data analysis.
Predictive analytics and artificial intelligence
Use data mining, machine learning and deep learning to identify patterns and develop predictive solutions. Explore text mining and social network analysis to work with different forms of data.
Students will come to understand subtle and profound differences between multinational and global marketing risks. It is essential for marketing managers to learn how to cope with risks of all types at the global level.
Big data and business applications
Work with big data technologies and Apache Spark, and learn how to move from an analytical model to a business application. Develop an applied Master’s Thesis across both semesters.
Master’s Thesis
The Master’s Thesis runs across both semesters, with 6 ECTS in each. It provides an opportunity to apply the programme’s methods to a practical data and business analytics project.
International Experience
Broaden your perspective with the opportunity to spend one semester at a European partner university through Erasmus+. An international study experience can help you develop independence, intercultural skills and a wider understanding of how data and technology are used in different settings. Contact CEDEU’s International Office for information on destinations and the application process.
More Information
Who is this programme for?
University graduates and professionals interested in using data to solve business problems, improve processes and support strategic decisions, particularly those with backgrounds in business, economics, engineering, technology or quantitative disciplines.
General competencies
- Translate business needs into analytical objectives and projects.
- Prepare, integrate and analyse information from different sources.
- Apply statistical techniques and predictive models to business problems.
- Communicate findings through dashboards, visualisations and reports.
- Evaluate the business impact of analytical solutions and manage data responsibly.
Entry requirements
A valid passport and an academic certificate or transcript confirming completion of a bachelor’s degree or equivalent qualification.
Frequently asked questions
Where and when will I study?
The programme is taught on campus at CEDEU in Madrid, in the Salamanca district. It lasts one academic year and carries 60 ECTS, with intakes in October and March.
What language is the programme taught in?
All teaching is in English. Spanish language lessons are also available for non-Spanish-speaking students.
How does the programme approach Python?
The study plan includes Python Fundamentals followed by Advanced Python, before moving into more specialised analytical methods and applications.
Do I need my own laptop?
Yes. Bring a laptop with at least 8 GB of RAM and a 256 GB SSD, with 50 GB of free space. For a smoother experience, 16 GB of RAM and a 512 GB SSD are recommended. You will need Wi-Fi, a webcam, a microphone and permission to install software. A dedicated graphics card is not required: cloud resources are used for relevant exercises. Required software is free or provided by CEDEU.
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