Introduction to artificial intelligence
Introduction to artificial intelligence
Learn the basic concepts of Artificial Intelligence and its practical applications, see the mathematical bases, calculus, linear algebra, probability. Supervised, unsupervised, reinforcement learning, see the different classifiers, cross-validation, discriminant analysis, classification trees and the basic operation of artificial neurons
Attended session
Friday 7 June · 10:00h - 14:00h
Attended session
Friday 14 June · 10:00h - 14:00h
Cibernàrium-22@, Carrer Roc Boronat, 117 - 127, (Sant Martí) BARCELONA
Language: Catalan
OBJECTIVES
- Learn how neural networks work, learn learning methods, learn classification methods, learn to create a neural network
SYLLABUS
- What is AI?
- Practical applications of AI
- What are and how do neural networks work?
- Mathematical bases used
- Learning methods (Supervised, unsupervised, reinforcement)
- Classification methods (Cross-validation, discriminant analysis)
- Configuration of model layers
- Image classification + Basic text classification
- GPT, language models and generative AI
Information not available
>> In case the format is virtual via streaming, it will be carried out through the free platform Microsoft Teams. Registered individuals will receive the invitation link and access instructions by email before the session starts.
>> Entry to the classroom will not be allowed after 15 minutes once the activity has started.
>> The language in which each session is conducted is informed in the description of each activity.
>> Any of the training actions of Cibernàrium may be recorded through an image capture system that aims to subsequently disseminate them through a medium or support within the scope of the mission of Barcelona Activa to contribute to economic promotion and employment. In the recording process, images of attendees may eventually be recorded. Registration for Cibernàrium activities implies authorization for Barcelona Activa to use these images for the aforementioned purpose.
Session types: Multisession
Duration: 8 hours
Lesson taught by
Information not available
