It is considered relevant for the present program that students can shape part of their space engineering curriculum according to their interests and motivations, in a personalized way. To this end, this subject includes mainly a set of optional subjects. The optionality also has a double benefit: it allows first to monitor the topics of greater demand and interest on the part of the students and secondly to adapt every few years the offer of courses to the new trends in space engineering.
Given that the number of elective courses is equivalent to 5 of 3 ECTS each, the offer of the master will be equivalent to 10 courses of 3 ECTS. A minimum number of students enrolled is required for the courses to take place. This number cannot be, in any case, higher than 50% of students enrolled in the master.
In-company internships are offered within this subject, optionally. In the same way, students will be able to participate in supervised development projects, in which they would work in a practical and specialized way some of the aspects dealt with in the previous subjects (1-4).
In the same way, those subjects of other masters that cover topics of interest for space engineering will also be considered within this matter. Finally, this matter will include, within the optional offer, regulated mentoring of students by professionals in the space sector.
Specific topics to each subject:
Big Data for Space Missions.
The program of this subject includes: statistics for data analysis; technological fundamentals in the Big Data world; optimization for large-scale data; machine learning; data analytics.
3. Big Data Processing
a. Supervised Machine Learning for Data Transmission
b. Unsupervised Machine Learning for Data Transmission
c. Data Batch Processing (Hadoop / Spark)
d. Data Processing in Streaming (Spark/Storm/Flink)
e. Big Data Storage and Management
f. Balancing Processes Architectures in backends varnish, kafka
g. Scalable Big Data Stora in NoSQL Databases cassandra / Hbase