In today's world, digital skills are not simply skills for programming or dealing with technology. They are skills for thinking and planning for a digital world, for analyzing problems and formulating solutions that can be executed automatically by an information processing machine.
Added to the challenge of dealing with technology is the need to understand how the global world works, the knowledge economy, networks, the spread of ideas, contagion, influence and the decisions that affect our lives.
At the same time as launching a new degree in Applied Data Science, Católica proposes an advanced training program in Digital Skills / Data Science aimed at professionals who, from teaching to companies and local authorities, are faced with the need to update their training in a practical way that is compatible with their usual work.
Course structure and timetable
The program consists of 20-hour modules, which are developed in 10 2-hour sessions, each consisting of a theoretical proposal and a practical challenge to be developed during the session, in an accompanied manner, and which can be chosen individually.
Initially, the sessions will be completely distance learning and the practical component will be carried out on the https://colab.research.google.com/.The modules take place on different days of the week, from 5pm to 7pm, for 10 weeks, so that the same student can attend as many as they wish.
This program will have up to three editions a year, one before Christmas, another between Christmas and Easter and a third after Easter, depending on the number of applicants.
General learning objectives
Acquire a strong spirit of computational thinking, of understanding machines as products of the human mind.
Develop technical skills appropriate to the study of situations involving the research and analysis of data, the discovery of information or the construction of knowledge based on the use of computers or programmable machines.
Modules
Modular format, modules that can be selected individually:
- Programming with Python (algorithms, data structures);
- Advanced Python (NumPy, Requests, matplotlib);
- Data analysis with Python (Pandas and csv files);
- Social network analysis with Gephi;
- Recommendation systems and collaborative filters.
