Objectives of the training
Upon completion of this course, you will be able to collaborate in decision-making involving concepts and principles of artificial intelligence (Machine learning and Deep learning) in the context of business projects.Targeted audience
Programmers, programmer analysts, IT project managers, IT directorsPrerequisite
Participants must be able to draw upon basic programming and mathematical notions (linear algebra, statistical probabilities). Basic knowledge of the Python programming language and the Jupyter environment is an asset.Trainers
Benefits for Participants
Course architecture
- Business applications of Artificial Intelligence
- Creation of an AI team
- Implementing a project: skills required, different steps of AI project
- Data to rely on: internal (company data), acquired externally
- Machine learning: the principles of learning and essential concepts
- Supervised and non-supervised learning
- Examples of machine learning use: classification, regression, image recognition
- Traditional machine learning models: linear, decision tree, SVM, etc.
- Deep Learning models: Transfer Learning and recurrent networks
- Python programming
- Libraries and tools
- Local and Cloud platforms
Pedagogical details
Training architecture
Practical: 20% Theoretical: 80%
Type of training
Private or personalized training
If you have more than 8 people to sign up for a particular course, it can be delivered as a private session right at your offices. Contact us for more details.
Request a quotePrivate or personalized training
If you have more than 8 people to sign up for a particular course, it can be delivered as a private session right at your offices. Contact us for more details.
Request a quote