This course provides a practical introduction to Machine Learning and Deep Learning.
Duration
2 days
Schedule
See training dates for details
Regular fee
$1,035
Preferential fee
A preferential rate is offered to public institutions, to members of certain professional organizations as well as to companies that do a certain amount of business with Technologia. To know more, please read the "Registration and rates" section on our FAQ page. Please note that preferential rates are not available for online training courses. Discounts cannot be combined with other offers.
$930
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
Associations and Partners Companies
Benefits for Participants
- Unit 1 – Basics of machine learning
At the end of this unit, participants will be able to provide a brief summary of the basic components of an AI problem .
- Unit 2 – Automatic learning algorithms
At the end of this unit, participants will be able to describe the key AI algorithms used to resolve simple problems.
- Unit 3 – Different steps of a corporate AI project
At the end of this unit, participants will be able to describe the process of preparing textual data taking into account the potential presence of bias.
- Unit 4 – Introduction to neural networks
At the end of this unit, participants will be able to describe the characteristics of deep learning
- Unit 5 – Recurrent and convolutional neural networks
At the end of this unit, participants will be able to describe the characteristics of recurrent and convolutional neural networks.
- Unit 6 – Launch of AI and its implications
At the end of this unit, participants will be aware of the risks associated with inexperienced or fraudulent use of artificial intelligence
Course architecture
Training eligible for SCALE AI grants
- Artificial Intelligence for business:
- 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
- Theory and applications:
- 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
- Implementation:
- Python programming
- Libraries and tools
- Local and Cloud platforms
Pedagogical details
Training architecture
Practical: 20% Theoretical: 80%
Type of training
Skill development
Skill development and knowledge integration
Decision support
Basic knowledge
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 quoteDuration
2 days
Schedule
See training dates for details
Regular fee
$1,035
Preferential fee
A preferential rate is offered to public institutions, to members of certain professional organizations as well as to companies that do a certain amount of business with Technologia. To know more, please read the "Registration and rates" section on our FAQ page. Please note that preferential rates are not available for online training courses. Discounts cannot be combined with other offers.
$930
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 quote