We may earn an affiliate commission when you visit our partners.
Course image
Yoshua Bengio and Sébastien Lemieux

Ces nouvelles méthodes permettent de développer de nouveaux outils d’aide à la décision pour les professionnels du domaine de la santé, comme par exemple l’aide au diagnostic de maladies par imagerie médicale, les soins de santé personnalisés, la découverte de nouveaux médicaments ou encore une meilleure analyse des risques.

Read more

Ces nouvelles méthodes permettent de développer de nouveaux outils d’aide à la décision pour les professionnels du domaine de la santé, comme par exemple l’aide au diagnostic de maladies par imagerie médicale, les soins de santé personnalisés, la découverte de nouveaux médicaments ou encore une meilleure analyse des risques.

Le contenu sera présenté à l’aide de vidéos pédagogiques présentés par des experts scientifiques: Tristan Sylvain, Gaétan Marceau-Caron, Jeremy Pinto, Margaux Luck, Joseph Paul Cohen et Tariq Daouda.

Two deals to help you save

We found two deals and offers that may be relevant to this course.
Save money when you learn. All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.

What's inside

Learning objectives

  • Développé en collaboration avec le mila et l'iric, ce cours présente :
  • Les concepts fondamentaux en science des données, en apprentissage automatique et profond appliqués au secteur de la santé;
  • Une introduction aux outils informatiques;
  • Des applications concrètes de ces méthodes et outils à différents domaine de la santé.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Adapté aux professionnels de la santé ou aux étudiants intéressés à appliquer des méthodes d'IA à ce secteur
Conçu en collaboration avec le Mila et l'IRIC, des institutions reconnues en intelligence artificielle et en recherche biomédicale
Présenté par des experts scientifiques du domaine, garantissant la qualité et l'actualité des informations
Couvre une large gamme d'applications, de l'aide au diagnostic à la découverte de nouveaux médicaments
Nécessite des connaissances de base en informatique ou en mathématiques, ce qui peut être un prérequis pour certains étudiants

Save this course

Save Science des données et santé to your list so you can find it easily later:
Save

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Science des données et santé with these activities:
Familiarize yourself with machine learning concepts
This course requires a basic understanding of machine learning. Following these tutorials will help you prepare.
Browse courses on Machine Learning
Show steps
  • Go to YouTube or other video platforms and search for tutorials on machine learning.
  • Choose a tutorial that is suitable for your level of knowledge.
  • Watch the tutorial and take notes on the key concepts.
  • Try out the examples and exercises provided in the tutorial.
  • Complete at least 3 tutorials to become comfortable with the basics of machine learning.
Gather Course Materials
Start preparing while waiting for this course to begin. Gather assigned readings and organize your classroom binder. Set up your study space.
Show steps
  • Create a dedicated course folder for handouts and assignments.
  • Purchase or download course textbooks and assigned readings.
  • Print out course syllabus and course schedule.
  • Set aside a dedicated time and space to study this course.
Review linear algebra
Review key concepts in linear algebra to ensure a strong foundation. This will enable you to better understand the application of these concepts in data science and machine learning.
Browse courses on Linear Algebra
Show steps
  • Go through your linear algebra lecture notes.
  • Watch online tutorials on linear algebra concepts.
  • Solve practice questions on matrices, systems of linear equations, and vector spaces.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Join a study group
Connect with other students taking the course. Regular study sessions will enhance your understanding and provide a support system during the learning journey.
Show steps
  • Reach out to fellow students through the course discussion forum or social media.
  • Set up regular study sessions to discuss course materials, solve problems, and prepare for assessments.
Python coding exercises
Practice writing Python code to strengthen your programming skills. This will help you implement data analysis and machine learning algorithms effectively.
Browse courses on Python
Show steps
  • Enroll in an online Python course or coding challenge platform.
  • Solve coding exercises on data manipulation, visualization, and algorithm implementation.
Learn scikit-learn library
Become familiar with the scikit-learn library for machine learning in Python. This will equip you with the tools necessary to build and evaluate machine learning models.
Browse courses on scikit-learn
Show steps
  • Follow online tutorials on using scikit-learn for data preprocessing, model training, and evaluation.
  • Explore the scikit-learn documentation and API reference.
Build a machine learning model
Apply your knowledge by building a machine learning model for a real-world dataset. This will give you hands-on experience in the entire data science workflow.
Browse courses on Machine Learning Model
Show steps
  • Select a dataset and define the problem statement.
  • Preprocess the data and explore its characteristics.
  • Train and evaluate different machine learning models.
  • Write a report summarizing your findings and insights.
Become a course mentor
Share your knowledge and skills by becoming a mentor for new students in the course. This will reinforce your understanding while helping others succeed.
Show steps
  • Apply to become a course mentor through the university or platform.
  • Provide guidance, support, and encouragement to new students.
  • Answer questions, facilitate discussions, and create resources for fellow learners.

Career center

Learners who complete Science des données et santé will develop knowledge and skills that may be useful to these careers:

Reading list

We haven't picked any books for this reading list yet.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Here are nine courses similar to Science des données et santé.
Introduction à l'apprentissage profond
Most relevant
Les médias numériques pour améliorer les résultats de...
Most relevant
Introduction à la science des données sociales avec R
Most relevant
L'essentiel de l'apprentissage profond
Most relevant
Recherche opérationnelle: optimiser ses décisions
Most relevant
Programmation et Politiques Financières, Première Partie:...
Most relevant
Données au service de la santé de la population
Most relevant
Fondamentaux de la science des données
Most relevant
Agents pathogènes chez le porc et la volaille
Most relevant
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2024 OpenCourser