Online Training
Maestría in Data Science for Business + 75 ECTS Credits
16 months
75CR
Spanish
Educational institutions


Request information
Online Training
16 months
75CR
Spanish
Educational institutions


Request information
Multilingual support
Digital certificate included
Assistant Phia
- Develop skills to apply data analysis and mining techniques in business environments. - Understand the impact of Big Data and its strategic value in decision making. - Use business intelligence and visualization tools to interpret data. - Apply advanced statistical methods to solve business problems. - Implement machine learning and automatic learning in process optimization. - Develop skills in artificial intelligence focused on the business field. - Handle Big Data tools for analysis and storage in organizations. - Design and develop research projects in data science applied to business. - Cultivate ethical and creative leadership in analysis and data science teams. - Integrate advanced technology and techniques Business Analytics in organizational strategy.
Data Analyst (Data Analyst) in technology and business companies. Data Scientist, specialized in Big Data and machine learning. Consultant in Business Analytics, advising on data-based strategies. Business intelligence manager (BI Manager) in organizations from different industries. Big Data specialist for massive data storage, processing and analysis. Director of data analysis and strategy in corporations and startups. Analyst Business Intelligence, focused on visualization and process optimization. Developer of predictive models and machine learning in areas of marketing and finance. Researcher in data science and analysis technology at universities and innovation centers. Trainer in data science and Big Data in educational and corporate institutions.
In the Maestría In Data Science we will prepare you to learn and develop all the concepts and tools, both technical and analytical, to be able to tackle a Big Data project with guarantees: from the most core part of Big Data (Hadoop), through data processing (Hive, Spark, etc.), NoSql data storage and ending with the area of analytics (Machine learning, model creation, visualization, etc.).