Master in Big Data
IMF Smart Education
Key Information
Campus location
Online Spain
Languages
Spanish
Study format
Distance Learning
Duration
24 months
Pace
Part time
Tuition fees
EUR 850 / per year *
Application deadline
Request info
Earliest start date
Sep 2024
* Base Price: €8,500
Scholarships
Explore scholarship opportunities to help fund your studies
Introduction
The Master in Big Data, co-developed with the technological multinational Indra, provides an overview of Big Data technologies and their use, as well as applied and practical training in analytical techniques for business (Business Analytics), that is, in the application from Data Science techniques to business problems.
Thus, the program responds to the need to know in a practical and applied way the use of technologies and data analysis methods. The understanding of technical use complements the business vision, so that graduates of the program will be able to reason in depth about the applicability of technologies, as well as apply analytical techniques and tools in specific situations.
Why study at the School of Artificial Intelligence & Big Data?
active experts
Active professionals from Indra and Minsait will teach you the skills and knowledge they seek for their teams
Design your custom training
Our programs are structured around 2 main axes, your profile and professional experience so that you can access the professional market from a technical (Hard tech) or business (Soft Tech) profile.
Learning by doing
It works with the clouds of the main players in the sector, ecosystems and open source platforms that serve +500 million people
Access to practices
Preference for access to professional internships with a minimum number of internships for each program
Degrees
By completing this program you will obtain a triple degree of Master in Big Data from IMF Smart Education , professional certification from Indra and Master of Big Data from UCAV.
Triple degree: IMF Smart Education + Indra professional certification + UCAV
Possibility of hiring internships and preferential access to selection processes
Ideal Students
The program is aimed at professionals and recent graduates of different profiles who want to orient or reorient their professional career to one of the emerging professions related to data analysis. Profiles can be of three types:
- ICT profiles: computer scientists, or related engineering, or professionals who have developed their careers in software development or IT systems administration.
- Quantitative profiles: graduates in careers with a strong quantitative component, such as statistics and mathematics, who want to expand their skills with data acquisition, storage and management techniques, as well as acquire new analytical skills.
- Business profiles: graduates and professionals in different areas of business and economics who want to specialize in business analytics, acquiring a solid background in the use of statistical languages and in understanding technology, not only at the business level, but in terms of to your technical application
Admissions
Scholarships and Funding
Program Outcome
- Understand the value of data and its analysis in organizations and be able to ideate and conceive data analysis solutions.
- Know and know how to state the business value of the main parallel processing and scalable data storage technologies, as well as know how to explain their use for specific purposes within the organization.
- Be able to apply data analysis techniques and methods to business problems using statistical programming techniques.
- Apply machine learning and text mining techniques to extract value from data and build predictive models.
- Know and know how to apply business intelligence and visualization tools to support analytics and decision making.
- Data analyst (Big Data Analyst).
- Data Scientist.
- Business Intelligence professionals.
- Chief Data Officer (CDO).
- Big Data Architect.
- Data Engineer
- Teacher in Business Intelligence courses
- Teacher in Data Analysis course
- Teacher in question Qlik
Career Opportunities
The program provides basic training to orient yourself to different professions within the area of data analysis and management; specifically: Digital Transformation Consultant
- Data analysts.
- Business Intelligence professionals.
- data scientists.
In the case of those profiles with previous experience in leadership and team management, the program will train them for positions such as Chief Data Officer (CDO). Finally, for professionals who have computer profiles, it will provide the basis for professional opportunities such as Big Data architect or Data Engineer.
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 acquired, whether for entering 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.
Data processing fundamentals for data science
- Using virtual machines and command shell
- Python programming fundamentals
- Relational Database Fundamentals
- Fundamentals of internet technologies
- Share data, code and resources in repositories
- Fundamentals of data processing with the Python scientific stack
Business Intelligence
- Introduction to business intelligence
- Data warehouses and analytical databases
- Removal and loading tools
- Business intelligence applications
- Big data analysis applied to business
- Customer intelligence (CRM)
Applied Machine Learning
- Introduction to machine learning
- Supervised models
- Unsupervised models
- Feature engineering and model selection
- Connectionist models
- Association rules and market basket analysis
Text Mining and Natural Language Processing (NLP)
- Historical and technological introduction
- NLP Tools I: NLTK
- NLP II Tools: Brat and Gate
- text mining
- Other NLP applications and techniques
Business intelligence and visualization
- Introduction to business intelligence
- BI vs. traditional reporting
- Technological foundations for data processing and analysis
- Data visualization fundamentals
- Advanced data visualization
- Visualization tools
Big data infrastructure
- Data processing with Hadoop
- Hadoop ecosystem tools
- Data processing with Spark
- Streaming architectures
- Components of streaming architectures
- Cloud platforms and APIs
Data storage and integration
- Unconventional databases
- Document-based database models
- Column-oriented database models
- Graph-oriented database models
- Key-value database models
- Data acquisition
Value and Context of Big Data Analytics
- The big data business case
- Big data projects
- Analytical applications by sectors
- Emerging technologies in analytics
- Team management and agile methods
- Regulatory aspects of data processing
Analytical Applications. Practical cases
- Scalable analytics: Analysis with parallel and scalable computing technologies
- Social media analytics
- Internet of things (IoT)
- Financial analytics (company rating)
- Customer analytics: location analytics
- Information recovery techniques
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
Beginner's course in Python
- 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
- Functions
English course
- Basic, Preintermediate, Intermediate or Advanced
- The student can choose one of the four levels.