Title: Introduction to Big Data and Artificial Intelligence in Public Health
Keywords: Technology
Informatics
Country: Morocco
Institution: Morocco - École Nationale de Santé Publique
Course coordinator: Fatima Eddaoudi
Date start: 2022-05-09
Date end: 2022-05-13
About duration and dates: One Week (5 days)
Classification: advanced optional
Mode of delivery: Face to face
Course location: ENSP, Rue Lamfedel Cherkaoui, Madinate Al Irfane ;BP 63 29: Rabat
ECTS credit points: 1.5 ECTS credits
SIT: A total of 40 Hours are dedicated to this training
‒ Self-study hours : 15Hours (during the training )
‒ Class attendance : 25Hours (during the training )
Language: French
Description: The objectives of this training are twofold. First, to introduce healthcare professionals to the concepts of artificial intelligence (AI) and Big Data. Then to make them aware of the interest of these technologies to reduce their workload while improving patient care.

At the end of this training, the student should be able to:

- Identify the stages of an AI solution development project in healthcare
- Identify the sources of health data including open data
- Identify the ethical and legal issues raised by an AI project in health;
- Differentiate the terminology related to: Artificial Intelligence, Deep Learning, Machine Learning, and Big Data
Assessment Procedures: The assessment in relation to the learning outcomes is organized during the training. The assessment methods are based on:

● individual work based (60%): the participant is required to prepare an written individual project that must be submitted at the end of the training. this project must propose a project based on the use of AI and Big Data in a health field. identify the steps for its implementation, while taking into consideration the ethical aspects. The last day of the training will be devoted to the presentation and discussion of these individual projects.
● Examination using a Multiple Choice Questionnaire MCQ (40%): two 20-minute MCQ assessments will be scheduled, one at the end of the 2nd chapter and the second at the end of the 4th chapter

Students who did not succeed the assessments will re-sit the examination using ENSP e-learning platform one or two weeks later.
Content: 4 Chapters:

Chapter I: Introduction to Big Data in Health (3Hours)
- Concepts and definitions
- Applications of Big Data in healthcare
- Telemedicine and e-health

Chapter II: Health data sources (8Hours)
- Data typology and Data sources in health
- Connected objects
- Digital patient records

Chapter III Introduction to Artificial Intelligence in Health (10 Hours)
- Concepts and definitions
- Fundamentals of Artificial Intelligence
- Areas of application of AI in health

Chapter IV Ethics of Big Data and AI in Health (4 Hours)
- Ethical aspects of AI
- Regulatory issues of AI in research
- State of the regulation of AI in health in Morocco
Methods: The teaching methods used consists of:
- Lectures followed by discussions (15h)
- Group work (5h)
- Case studies (5h)
- Self-learning (15h)
Prerequisites: Academic degree:
Bachelor degree or master degree in: public health, management, data sciences; physician, nurse, pharmacist

Language:
- Required French level C1 (If the candidate does not have certificates to demonstrate the required level, an oral and writing test via e-mail and skype will be organized)

- The participant must be familiar with health projects management
- The participant must be familiar to databases
Attendance: A maximum of 30 Students including 10 troped students
A minimum of 10 students is required to launch the training
Selection: Participants are selected based on a Skype interview during 20 minutes. The selection is based on the candidate's motivation to follow the course

If a minimum of 10 participants is not reached, the course will be canceled and participants will be notified one month in advance.
Fees: 6000 MAD (600 Euros)
Scholarships: NA
tropEd accreditation: Accredited after EC phone conference July 13, 2021. Valid until July 2026.
Email Address: raja.benkirane@gmail.com
Date Of Record Creation: 2021-07-28 02:00:16 (W3C-DTF)
Date Of Record Release: 2021-07-28 07:10:19 (W3C-DTF)
Date Record Checked: 2021-07-28 (W3C-DTF)
Date Last Modified: 2021-11-21 19:10:42 (W3C-DTF)