Learning objectives
At the end of the course, the student will have acquired:
- knowledge related to the functioning of computing machines for the digitization of information
- knowledge of application programs for data organization and analysis and preparation of presentations
- the ability to apply these IT tools to real cases of clinical-professional interest
- knowledge related to the responsible consultation of the web for the retrieval of scientific literature data
- knowledge of technologies based on artificial intelligence algorithms for the automated analysis of data and time series in the biomedical field
Prerequisites
Basic elements of Mathematics. Basic use of computer.
Course unit content
Computer architecture.
The representation of information (binary coding). Operating systems and programming languages for data analysis in the scientific field. Software for text production, organization and graphical representation of data, production of presentations (Office package: Word, Excel, Power Point). Data collection by consulting the main scientific literature databases and data organization into datasets. Introduction to artificial intelligence techniques for the automatic analysis of data and time series in the biomedical field.
Full programme
Computer architecture (main components, peripheral units, main and secondary memories, CPU, BIOS). The representation of information (binary coding). Operating systems and programming languages for data analysis in the scientific field. Software for text production, organization and graphical representation of data, production of presentations (Office package: Word, Excel, Power Point). Data collection by consulting the main scientific literature databases and data organization into datasets. Introduction to artificial intelligence techniques for the automatic analysis of data and time series in the biomedical field.
Bibliography
The slides used by the teacher during the lectures will be available on the MOODLE Portal page, or will be shared to the class representative (in compliance with copyright).
Teaching methods
Teaching is delivered through lectures that are carried out with the help of audiovisual equipments (Power Point presentations). The course is delivered in Italian. For health emergencies following institutional directives, the lessons could be delivered remotely limited to the emergency period. Lectures will be alternated with guided laboratory activities (hands-on sessions on examples and applications).
Assessment methods and criteria
25-minute written exam including 21 closed questions. The questions have 5 answer options, only one of which is correct. The correct answer is awarded 1.5 points, the unsuccessful or incorrect answer 0 points. The grade reported in the exam is given by the sum of the points obtained (a score greater than 30 results in obtaining a grade of 30 with honors). Non-binding prerequisite for admission to the written test will be the production of a presentation developed in the Office environment on a specific case of data collection and processing from scientific literature.
Other information
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2030 agenda goals for sustainable development
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