Categorías:
Otros
Etiquetas:
artificial intelligence
artificial neural networks
Chat GTP
deep learning
knowledge representation
Machine Learning
Natural Language Processing
network analysis
ontology engineering

ARTIFICIAL INTELLIGENCE

 

Course Dates: 22 to 26 July 2024

Course Venue: School of Computer Systems Engineering, Classroom 1301

Contact Hours: 20

Course Directors: María Póveda & Víctor Rodríguez

 

PART I: Introduction to Artificial Intelligence

 

Artificial Intelligence (AI) refers a kind of intelligence that enables machines to emulate intelligent behavior or to do things that people mostly do better. AI technologies have an important impact on our daily activities in business, as individuals, and as a society. During this course, apart from learning about AI fundamentals and applications, you will use specific techniques about different areas of AI such as knowledge representation and machine learning.

 

PART II: Deep Learning

 

Deep learning, a cutting-edge subset of artificial intelligence, is increasingly pivotal in driving technological and scientific advancements across various sectors. This comprehensive course on the fundamentals of deep learning is thoughtfully designed to guide students through the core concepts and applications of this transformative technology. It begins with an introductory module that lays a solid foundation in the basics of deep learning and artificial neural networks. The course then progresses into the practical realms of computer vision, demonstrating how deep learning techniques are revolutionizing image analysis and interpretation. In the natural language processing (NLP) module, students will explore the ways deep learning is used for understanding and generating human language, a critical aspect of AI's interaction with people in products such as ChatGPT. The course also includes a focus on network analysis, where the course delves into graph neural networks and their role in predicting complex network dynamics. Each theoretical component is complemented by hands-on activities, ensuring a balanced approach that combines conceptual knowledge with practical skills, fostering both understanding and application in this rapidly evolving field.

 

Key course takeaways:

  • Understanding of concepts, foundations, methodologies and technologies of artificial intelligence, machine learning and the semantic web and linked data, open data, data representation languages and web ontologies

  • Overview of practical applications of AI technology in the real world

  • Solid grasp of the basic concepts, theories, and historical context of deep learning, understanding its role as a key driver in modern artificial intelligence

  • Ability to apply deep learning concepts to real-world tasks, gaining practical experience in various domains such as computer vision, natural language processing, and social network analysis

  • Analytical skills, enabling participants to critically assess and solve complex problems using deep learning techniques, fostering a mindset for innovation and solution-oriented thinking

  • Hands-on experience with the tools and frameworks commonly used in deep learning, preparing participants to effectively implement and manage deep learning projects

  • Knowledge and skills necessary for advanced study in the field or to enhance their career prospects in industries where deep learning is relevant

  • Preparation to adapt to and embrace emerging trends and innovations in deep learning, ensuring they remain current and relevant in this rapidly evolving field

 

Student profile:

This course is aimed at bachelor-level students.

 

Registration deadlines:

  • Early bird registration:  29 February 2024 (USE CODE: SUMMEREB24)
  • Regular registration: 19 April 2024

La inscripción ha finalizado.

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