Master in Data Science and Business Analytics co-developed by Indra
DURATION
24 Months
LANGUAGES
Spanish
PACE
Full time
APPLICATION DEADLINE
Request application deadline
EARLIEST START DATE
Sep 2024
TUITION FEES
EUR 850 / per year *
STUDY FORMAT
Distance Learning
* online final price - €442
Scholarships
Explore scholarship opportunities to help fund your studies
Introduction
This master's degree has 52% scholarships! Find out before February 16
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- Con el Máster en Big Data aprenderás el conocimiento y experiencia práctica de profesionales que combinan un background técnico sólido y la aplicabilidad de las tecnologías, mediante el uso de la tecnología, utilizando las herramientas software que se aplican en entornos profesionales para obtener una formación en el área de Big Data Analytics y Business Analytics de manera flexible.
- En el Máster en Data Science y Business Analytics se parte de los fundamentos de la ciencia de datos, aprendiendo lo necesario para ser capaces de procesar, analizar e interpretar todo tipo de fuentes de información, hasta llegar a la analítica avanzada que incluye el uso de técnicas de inteligencia artificial, en especial las que tienen que ver con machine learning y deep learning.
La respuesta a muchas de las preguntas de negocio está en datos, y cómo interpretarlos y ser capaz de tomar decisiones en base a ellos es lo que demanda el mercado. Con este programa podrás adquirir estos conocimientos sin necesidad de un background técnico.
El Máster en Data Science responde a las necesidades formativas de aquellos profesionales que sin tener un background técnico quieran introducirse en el mundo del Data Science & Big Data. Durante el mismo, se conocerán las tecnologías y herramientas necesarias para la gestión de un proyecto de Data Science & Big Data, las distintas aplicaciones en el mundo empresarial con talleres prácticos y las nuevas tendencias dentro del sector.
¿Por qué estudiar en la La Escuela de Inteligencia Artificial & Big Data?
Expertos en activo
Profesionales en activo de Indra y Minsait te enseñarán las skills y conocimientos que buscan para sus equipos
Diseña tu formación a medida
Nuestros programas se estructuran en torno a 2 ejes principales, tú perfil y experiencia profesional para que accedas al mercado profesional desde un perfil técnico (Hard tech) o de negocio (Soft Tech)
Learning by doing
Trabaja con las clouds de los principales players del sector, ecosistemas y plataformas de código abierto que dan servicio a +500 millones de personas
Acceso a prácticas
Preferencia de acceso a prácticas profesionales con un mínimo de contrataciones en prácticas por cada programa
Titulaciones
Completando este programa obtendrás una triple titulación de Máster en Data Science por IMF Smart Education, certificación profesional por Indra y Máster de Data Science por UCAV.
Ideal Students
Profiles with a university degree in fields not related to STEM or professionals with at least 3 years of experience in the business environment. This program does not require computer knowledge or programming languages, since it is focused on the application of data to business and decision-making, once the data collection, treatment and storage phases have been overcome.
Career Opportunities
- Know current technologies and new trends in Data Science and Big Data projects to be able to manage a project of this type.
- Get started with new trends within the sector.
- Understand the applications of this type of projects in a sectoral manner with case studies and practical workshops.
Program Outcome
- Know current technologies and new trends in Data Science and Big Data projects to be able to manage a project of this type.
- Get started with new trends within the sector.
- Understand the applications of this type of projects in a sectoral manner with case studies and practical workshops.
Accreditations
Scholarships and Funding
Admissions
Curriculum
Master designed by a committee of experts made up of doctors and active professionals from leading companies in the field of Artificial Intelligence and Big Data such as Indra and Minsait. Their experience guarantees the suitability of the studies and the
skills that are acquired, either for incorporation into the world of work or for professional improvement in the sector. This team of experts, in addition to participating in the training program design committee, collaborates in the tutoring and delivery of the master's sessions.
The tools of the data scientist
- Python Fundamentals
- Libraries for data science: Numpy, Pandas, etc.
- Data processing and visualization with Python
- R Fundamentals
- R packages
- Data processing and visualization with R
Data science. Analysis, mining and visualization techniques
- The data life cycle
- Data quality
- Data preparation and preprocessing
- Analytical models
- Visualization tools and techniques
Statistics for data scientists
- Language and data processing
- Exploratory data analysis
- Probability and statistical inference
- Linear models and statistical learning
- Logistic regression, restricted Ridge and Lasso and gradient models
Machine learning
- Tools for machine learning
- Techniques and applications of supervised learning
- Techniques and applications of unsupervised learning
- Deep learning modalities and techniques
- Cloud solutions for machine learning
Artificial intelligence for the company
- Introduction to artificial intelligence
- Techniques and applications for decision making
- Reinforcement learning and applications
- Techniques and applications of natural language processing (NLP)
- Recommendation systems and applications
Big Data technology and tools
- Hadoop and its ecosystem
- Spark. Fundamentals and applications
- NoSQL databases
- Cloud Platform
The work of the data scientist: steps and techniques in analysis. Storytelling
- Introduction: data science concepts
- Steps in data analysis
- Storytelling: highlighting and transmitting the results of the analysis
The machine learning process: what it is and what it is not. Where to apply artificial intelligence
- Machine learning concept
- How to keep learning
- Typical use cases
New trends: process mining, MLOPs, cloud
- process mining
- Cloud
- MLOps
Master's thesis (TFM)
Agile Methodologies Course
- What is Scrum and how to apply it
- The Scrum Framework
- Self-organized teams
- The role of clients and stakeholders
- Agile product and project management
- Development and continuous integration
- How to evolve towards an agile organization
Python introductory course
- Introduction to Python
- Conditionals in Python
- Repetitive structures in Python
- Collections. Lists
- String functions
- Collections. Dictionaries
- Functions
- File management
- object orientation
Introduction to R course
- Introduction to R
- Vectors
- Matrices
- Lists
- Data Frames
- Control structures
- Features
English course
Basic, Preintermediate, Intermediate or Advanced
The student can choose one of the four levels.