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[JOURNAL]: "ARTIFICIAL INTELLIGENCE IN THE INDUSTRIAL SECTOR, CHALLENGES AND OPPORTUNITIES". Face-to-face mode

activity For your company!

Organizes this training tailored to your company! Contact us here
Addressed: Managers, company managers and engineers
Dates: 18 and 20 June 2024
Schedule: From 16.00 to 20.00 hours
Mode: On line
Duration: 8 hours
Assistants: Minimum 10
Schedule: From 16.00 to 20.00 hours
Goal:

- Understand the change of the digital transformation

- Acquire a global vision of the potential of data science

- Know the characteristics, needs and methodologies of working on an Artificial Intelligence project

- Know specific tools and methods of data analysis and Artificial Intelligence

- Types of solutions offered by Artificial Intelligence in the industrial field

- Hybrid solutions

- Requirements for the application of these techniques

- Ability to identify possible applications in real situations

- Understand the reason for success or failure in data analysis and the application of Artificial Intelligence

Programming:

1. Digitization

2. Big Data, data science and Artificial Intelligence

3. The new professional profiles

4. Development methodology for a Big Data and AI project

5. Artificial Intelligence Methods

6. Machine learning algorithms

7. Optimization in production processes

8. Predictive maintenance

9. Virtual sensors and simulations

10. Control and decision-making in the industrial field

11. Applications of Artificial Intelligence in the industrial field

12. Agile work methodologies

13. Data ethics and morality

Documentation: The documentation will be available on the platform between 24 and 48 hours before the start of the training. In the event that there is additional documentation once the training is completed, we will provide it to you later.
Certification:

Once the training has been completed, students will receive a certificate of attendance that can be downloaded from the platform.

Bonuses: We manage the procedures so that you can benefit from the corresponding training bonus.
Bonus instructions:

1. Request the forms from the CETIT at formacio@ingenijerstarragona.cat

2. Provide all the information 10 calendar days before the start of the course.

3. IMPORTANT NOTE: the bonuses are carried out by means of an external consultancy.

Those who wish to take advantage of the bonus for any training action, the price will be increased by 20% (which can also be bonused and recovered).

Conditions:

Cancellation of registrations:

Depending on the registrations made, the training action will be viable or not, for this reason it is important that you notify cancellations.

The cancellation must be communicated 48 hours before the start of the training through the email formacio@cetit.org, otherwise 100% of the amount of the training action will be invoiced.

Images and recording of the course: we inform you that, in compliance with the RGPD, the current legal regulations on data protection and Law 1/1982 on civil protection, right to honor, personal and family privacy and the image itself, photographs will be taken during the course and in certain cases they will be recorded and/or broadcast live. Under no circumstances will the name of the interested party be published. The image is used legitimately for the College's legitimate interest in promoting these courses and their possible subsequent viewing by attendees.

By attending, these images will be kept for as long as the course is uploaded to the platform. Once the time limit for later viewing has passed, it will no longer be uploaded to the platform and the images will be deleted with appropriate security measures.

Likewise, you have the right to request access, rectification, portability and deletion of your data and the limitation and opposition to its treatment by sending an email to dpd@cetit.org. For more information on data protection rights, access our website: http://www.ingenijerstarragona.cat/home/article/privacyt.

Speakers

  1. Núria Nievas ViñalsInvestigadora a la unitat de Intel·ligència Artificial Aplicada (AAI) d’Eurecat. Va estudiar el grau en Matemàtiques i en Administració i Direcció d'Empreses a la Universitat de Barcelona (UB). Posteriorment va obtenir un màster en Ciència de dades i Intel·ligència Artificial a la mateixa Universitat. Actualment és una estudiant de doctorat a la Universitat de Lleida d'intel·ligència artificial en l'àrea d'Aprenentatge per Reforç aplicat a la presa de decisions en l'àmbit industrial. El seu treball consisteix en el desenvolupament de processos d'optimització per a la direcció i presa de decisions en processos industrials i empresarials aplicant algorismes d'optimització multi-criteri, aprenentatge automàtic i aprenentatge per reforç. Com a investigadora està involucrada en projectes de R + D, tant a nivell europeu com nacional, relacionats amb optimització i gestió de recursos, anàlisi de dades, Intel·ligència Artificial i indústria 4.0..