MES2 - ECTS At the end of this course the student should be able to:
• Identify the challenges and requirements for persisting and analyse big data
• To know the development phases of BI/Analytics projects
• Modelling and specifying a Datawharehouse
• Understand the best practices for coding the ETL process
• Conduct analytical queries to a multidimensional Datawharehouse through SQL OLAP extensions
• Evaluate, select and configure OLAP systems
• Differentiate and select several datamining algorithm classes, and their usage assumptions
• Develop visualizations for data and respective analyses results reporting, over existing platforms

MES4 - ECTS

This Course Unit aims to develop students' capabilities in the area of web programming at the customer level (front-end development).

In the design of web applications particular attention will be given to issues related to Accessibility, mastery of its requirements, standards and implementation processes.

MES1 - ECTS This course presents high level aspects of software development.

The concept of quality invites the introduction of tecniques for project management, model definition and valitation, software testing on several layers of abstraction, and the use of quantitative metrics, from the basic unit level to the complete feature and integration level.

MES3 - ECTS At the end of this curricular unit the student should be able to:
- Understand the main paradigms and models of computer and information systems security.
- Understand how cryptographic algorithms and protocols work.
- Understand basic protection mechanisms.
- Recognize vulnerabilities of organizational information systems and software.
- Apply techniques, and algorithms and use tools to prevent and defend against attacks, enhancing information systems and software security.

MES8 - ECTS Provide students with the knowledge to develop mobile applications based on Web services.

MES5 - ECTS

At the end of this course, students will be able to:

• Identify the distinct levels of reusing software, identifying the technical and non-technical issues.
• Select and properly apply software architecture patterns in order to solve a specific problem.
• Select and use components and software libraries to solve a specific problem.
• Design and implement software libraries.
• Select and use software components to solve a specific problem.

MES6 - ECTS Know and understand the essential protocols, frameworks and methodologies for the development of information systems on the Internet, with a greater focus on the implementation of "backends".

MES7 - ECTS

1. To introduce students to the fundamental problems, concepts, and approaches in the design and analysis of data visualization systems.
2. To familiarize students with the stages of the visualization pipeline, including data modeling, mapping data attributes to graphical attributes, perceptual issues, existing visualization paradigms, techniques, and tools, and evaluating the effectiveness of visualizations for specific data, task, and user types.
3. To enable students to develop complex / advanced interactive information visualization systems.

MES11 - ECTS The objectives to be achieved are, in addition to the technical execution of the project, primarily as follows:
- develop the ability to address a real computer engineering problem, presenting a solution that can be implemented;
‐ provide students with a contact with the business reality, facilitating the approach to management practices and the practice of engineering, applied in companies

MES9 - ECTS

• Essential theories and concepts of digital marketing 
• Competitive analysis in social media 
• Content Marketing Strategy 
• Social Media Setup
• Web presence concepts and techniques 
• Google Analytics 
• Email Marketing 
• Social Network Analysis 
• Sentiment Analysis
• Search Engine Optimization 

MES10 - ECTS - Acquisition of knowledge for the formulation of a practical problem using pattern recognition techniques
- Ensure that students acquire the ability to implement and use various supervised and unsupervised classification algorithms
- Provide theoretical and practical skills to perform intelligent analysis of unstructured data, namely in texts, and in particular using common examples on the internet, such as web pages, asynchronous messages and e-mail, using the acquired pattern recognition techniques in this UC.