Course - detail

LCE5736 - Artificial Intelligence and Robotic Applied to Research and Management


Credit hours

In-class work
per week
Practice
per week
Credits
Duration
Total
2
2
8
15 weeks
120 hours

Instructor
Cristian Marcelo Villegas Lobos
Gabriel Adrian Sarries
Gabriela Maria Rodrigues

Objective
Introduce students in the areas of Artificial Intelligence (AI) and robotic preparing them for the job
market.Collaborate in the implementation of AI in dissertations, theses and articles for publication.
Introduce elementary concepts of programming languages in R, SAS, SQL and Python.

Content
1. Concept and applications of AI, Statistics and Robotics.
2. Impact of AI and Robotics technologies on humanity.
3. Supervised and unsupervised machine learning: regression models, classification methods,
dimensionality reduction methods and clustering methods. Resampling methods.
4. Inductive AI for numerical data mining and text mining. Data pre-treatment and visualization.
5. Development of applications and bots with AI. Analysis, design, prototyping, simulation, testing and
manuals for applications and AIR (AI Robots).
6. AI in each stage of the Scientific Method (SM).
7. Applications of AI in research (IA Conected Papers), business management, project management and
quality of life.
8. The methods and applications will be carried out with the support of software (R, Python and/or SAS).
The detailed program is on the website at https://sites.google.com/usp.br/lce5736-ia-n-basico

Bibliography
BORGES, L. E. Python para desenvolvedores. 2ª edição. San Francisco, California: Creative Commons,
2021. Disponível em:
. Acesso em: 6
jun. 2024.
BRITISH BROADCASTING CORPORATION. The Scientific Method. London, UK: BBC. Disponível em:
. Acesso em: 6 jun. 2024.
MORETTIN, P. A., SINGER, J. M. Estatística e Ciência de Dados. Rio de Janeiro: LTC, 2022. 464 p.
RUSSELL, S. J.; NORVIG, P. Artificial Intelligence: A Modern Approach (Pearson Series in Artifical
Intelligence) 4th Edition. Londres: Pearson, 2020. 1136p.
SAS Institute. Documentação Oficial do SAS. SAS Carolina do Norte, EUA, 2024. Disponivel em:
. Acesso em: 6 jun. 2024.
SICSÚ, A. L.; SAMARTINI, A.; BARTH, N. L. Técnicas de Machine Learning. São Paulo: Blucher, 2023.
394 p.
TAULLI, T. Introdução à Inteligência Artificial – Uma Abordagem não Técnica. São Paulo: Novatec. 2020.
232 p.
WICKHAM, H., & GROLEMUND, G. R for data science: Import, tidy, transform, visualize, and model data.
O'Reilly Media, 2016. 584p.
Izbicki, R. e Santos, T. M. dos. Aprendizado de máquina: uma abordagem estatística. edição. 2020. 272
páginas. ISBN: 978-65-00-02410-4
Friedman, J., Hastie, T., Tibshirani, R. (2001) The elements of statistical learning. Springer, New York.
James, G., Witten, D., Hastie, T., Tibshirani, R. (2013) An introduction to statistical learning. Springer,
New York.
Burger, S.V. (2018) Introduction to machine learning with R. O'Reilly Media, USA.