Universidad Pontificia Comillas
Master's Degree in Business Analysis
Madrid, Spain
Master degree
DURATION
1 year
LANGUAGES
Spanish
PACE
Full time
APPLICATION DEADLINE
EARLIEST START DATE
TUITION FEES
EUR 19,000
STUDY FORMAT
On-Campus
Key Summary
What can the Master offer you?
We are immersed in a great revolution. The incredible development in recent years of Artificial Intelligence and Machine Learning and Deep Learning algorithms, access to enormous volumes of information of all kinds, in which everything can be data (texts, images, audios, videos) and The democratization of access to analysis tools is permeating the entire economic, business and social ecosystem.
Today, decision-making in the environment of businesses, organizations and Public Administrations cannot be understood if they are not based on evidence and the support of sophisticated analysis models that allow patterns and relationships to be extracted to obtain value from the data. data and information. And this is just the beginning.
Do you want to understand this revolution and be part of it or stay behind without understanding the present? The Master's Degree in Business Analytics provides you with the knowledge and skills necessary to understand this world of data and models, know their practical application in different contexts and economic and business areas and know how to apply it to the resolution of real problems, building and applying your own models. Being able to have dialogue and bridge between the business field and the technical field.
- Advanced Business and Data Analyst
- Analytics and Digital Transformation Consultant
- Business Intelligence and Predictive Analytics Specialist
- AI-Based Solutions Developer
- Data Scientist and NLP Specialist
1º Semestre
- Digital Business 3.0 ECTS
- Business Analytics 3.0 ECTS
- Visualization 3.0 ECTS
- Machine Learning. Fundamentals and Supervised Learning 6.0 ECTS
- Machine Learning. Unsupervised Learning 3.0 ECTS
- Introduction to Programming 6.0 ECTS
- Sources and Databases 3.0 ECTS
- Innovation and Creativity 2.0 ECTS
2º Semestre
- Unstructured Data Analysis 3.0 ECTS
- Deep Learning 3.0 ECTS
- On the Border 3.0 ECTS
- Big Data and Internet Technologies 3.0 ECTS
- Ethical Challenges and Risks. Cybersecurity 4.0 ECTS
Business Analytics Applied Cases (choose 3)
- Data Analytics Applied to Finance 3.0 ECTS
- Forensic Audit 3.0 ECTS
- Data Analytics in Logistics and Supply Chain 3.0 ECTS
- Analytical Marketing 3.0 ECTS
- Data Analytics for Talent Management 3.0 ECTS
- Public Economics and Health 3.0 ECTS
- International Financial Trading 3.0 ECTS
- Entrepreneurship 3.0 ECTS
- Data-Driven Economic Analysis 3.0 ECTS
- Blockchain 3.0 ECTS
Competencias
- CP01. Be able to apply BA techniques, using real data sets and appropriate software or code, knowing how to interpret the results and communicate the main conclusions to non-technical audiences.
- CP02. Be able to fully carry out a BA application case to a real problem, from the description to the solution and the proposal of conclusions and recommendations.
Knowledge or Contents
- CO1. Know the main features and trends of the digital ecosystem, the main digital business models and the startup cycle
- CO2. Know and know how to apply strategic analysis tools in the digital world, with special emphasis on knowledge of the competition (Crunchbase, Buzzsumo, etc.) and trends (Google Trends)
- CO3. Know the concepts and language of Business Analytics techniques and methods, from descriptive ones to the main machine learning algorithms and models, both supervised and unsupervised, including visualization techniques.
- CO4. Know the concepts and language of advanced techniques and methods in Business Analytics, from the analysis of unstructured information, through neural networks and Deep Learning methods and new advances in the field of Artificial Intelligence, understanding their scope in business and society.
- CO5. Acquire sufficient programming proficiency to develop data analysis and machine learning projects, becoming familiar with data structures in Python (lists, dictionaries, dataframes), making advanced use of functions and methods from key libraries, and practicing data visualization.
- CO6. Intuitively understand the essential elements and concepts of technology linked to databases, information storage and retrieval, Big Data, the Internet and other connective technologies such as the 'Internet of Things', having a panoramic, critical and prospective view of all these topics.
- CO7. Know and know how to apply in a practical way techniques to promote creativity and innovation in the business field, with special emphasis on design thinking, Agile methodologies, Lean Start-Up, and gamification applied to problem solving.
- CO8. Know and have critical reflection on the main ethical challenges and risks associated with the implementation of Artificial Intelligence technologies, both in the business field and in society as a whole, including some issues related to cybersecurity and show a critical reflection on them.
Skills or Abilities
- HB01. Use the Business Analytics technique or techniques most appropriate to each real problem and the type of data available, knowing the requirements and limitations of its correct application.
- HB02. Create code examples (“toy examples”) primarily aimed at data analysis
- HB03. Fully understand the application cycle of data-driven Business Analytics techniques to identify and solve a real problem in some of the main application areas
- HB04. Compose an independent argument with rigor and precision and be able to present it both orally and in writing