- Code
- FD0139
- Type
- Specific and On-Demand Training Program Course - MICROCREDENCIAL
- Teaching Modality
- Semi-face-to-face
- Duration
- 1 year
- Credits
- 12.0
- Course
- 2022-2023
- Price
- 480,00€
- Center
- Centro Singular de Investigación en Tecnologías de la Información de la USC (CITIUS)
- Management
- Senén Barro Ameneiro
- Contact
mariajose.carreira [at] usc.es
Department / Organizing Center
Centro Singular de Investigación en Tecnologías de la Información de la USC (CITIUS)
MARIA JOSE CARREIRA NOUCHE
16431
mariajose.carreira [at] usc.es
Centro Singular de Investigación en Tecnologías de la Información de la USC (CITIUS)
Dates
Duration: 20/02/2023 - 27/06/2023
Pre-registration: 23/01/2023 - 30/01/2023
Registration: 06/02/2023 - 12/02/2023
Minimum number of students: 20
Maximum number of students: 40
Commentaries: Registration will be made after selection based on the criteria detailed in the "Access Criteria" section defined by the Committee of Experts promoting the course, made up of external experts and staff from USC and GSK. The target audience is health professionals (specifically, specialists in hospital pharmacy, oncology, hematology and technical personnel for pharmacoeconomic evaluation of the administration) interested in training in the application of Artificial Intelligence in oncohematology clinical practice, in particular in relation to concepts and tools for advanced data analysis and machine learning techniques. The course will be remote and will end with the presentations of the final projects in a face-to-face session.
Mandatory insurance:
17,50€ (Students who formally enroll in their own Postgraduate courses, Continuous Training and Training Program, will also be included the amount of mandatory accident insurance and travel assistance for USC students, as established in current regulations (Council Agreement Government June 29, 2009) and will be issued together with the 1st liquidation of registration. Except in the courses that are 100% virtuous, considered these by academic year; and in the cases in which the students have paid this same insurance in a USC degree in the current academic year.)
Access requirements
The course is aimed at personnel currently practicing their profession in Spain and belonging to one of the following profiles: a) Hospital Pharmacist Personnel with experience in Oncohematology, Resident Internal of 3rd year or higher. b) Medical Staff Specialist in Oncology or Hematology Internal Resident of 3rd year or higher. c) Technical staff for evaluation of health management and pharmacoeconomics. It is recommended that candidates have experience or basic knowledge of statistics. This knowledge will be valued in the selection criteria. Admitted people, to formalize the registration, must complete a document in relation to the declaration of the transfer of value by GSK. This document will be provided together with the communication of admission to the course. In addition, if they are technical personnel for the evaluation of health management and pharmacoeconomics, they must complete a document regarding their possible influence on the purchase or evaluation of medicines. This document will be provided together with the communication of admission to the course.
Pre-registration
You can consult a manual of the admission procedure on the CEP website in Archive or by clicking here
To apply for admission, go to the following link of the virtual secretary
https://matricula.usc.es/Posgrao/SolicitudeEstudosPropios
Access to pre-registration and registration
Selection system
Those established in the access requirements. If the applications that meet the requirements exceed the 40 available places, the admission criteria will be according to the order of registration.
Objectives
That the participants, at the end of the course, are able to understand and use AI techniques in their research and care activities.Specific objectives:
- Learn and consolidate the basic concepts to be able to launch and lead Artificial Intelligence projects in their hospitals / regions.
- Practice proposed exercises with low-code/no-code solutions (it is not necessary to program)
- Discuss the ideas of the students to identify potential risks: biases, reputation problems, reliability, etc.
- Focus of this practical training to achieve a 360º vision of AI
- Discover the problems that can be solved with machine learning, as well as the main AI-as-a-service algorithms and solutions
Career options
The course will be remote, with sessions in which each topic will be addressed and live master sessions (also available on a deferred basis) and practices. The students will carry out a final project that will be presented in a face-to-face session at the end of the course.Evaluation
Attendance to live or deferred sessions. To obtain certification, at least 85% of the sessions must be completed and a final project submitted.
Tutoring
The course is structured in 4 subjects, 1 personal project, and 4 master sessions.
Tuesday from 5:00 p.m. to 7:00 p.m. and Thursday 4 one-hour master classes. They can also be completed on a deferred basis in the virtual classroom. Tutorials will be scheduled on Mondays from 5:00 p.m. to 6:00 p.m.
Observations
If the dates vary, these will be communicated to the students well in advance.
| Code | Subject | Credits |
|---|---|---|
| 1 | Introduction To Ai: Fundamentals And Historical Journey. | 1.0 |
| 2 | Ai: Legal And Ethical Aspects. | 1.0 |
| 3 | Ai: Data/information Analysis Tools And Machine Learning. | 2.5 |
| 4 | Design Of Quality And Reliable Solutions. | 1.5 |
| 5 | Master Sessions. | 0.5 |
| 6 | Final Project. | 5.5 |