Short Course I: Introduction to Machine Learning (13-Oct, 9:30 to 11:00 and 11:30 to 13:00)

Prof. André C. P. L. F. de Carvalho (USP)

Many of the current computational tools that allow automatic and efficient data analysis are based on concepts from Artificial Intelligence, particularly Machine Learning. This course will present how Machine Learning techniques can be used for descriptive and predictive analysis. The material used in the course will be based on the book Inteligência Artificial: uma Abordagem de Aprendizado de Máquina, by Katti Faceli, Ana Carolina Lorena, João Gama e André C. P. L. F. de Carvalho, LTC.

Short Course II: Four Paradigms in Data Mining (13-Oct, 14:30 to 16:00 and 16:30 to 18:00)

Prof. Wagner Meira Jr. (UFMG)

Data mining encapsulates the process of exploring and extracting insights from large collections of data, and is commonly applied for the purposes of scientific discovery, business intelligence, processing Web data, and so forth. This short course will introduce four high-level paradigms in data mining; namely, combinatorial, probabilistic, algebraic and graph-based paradigms. For each paradigm, a number of concrete data mining algorithms will be presented. The short course will be based on the book "Data Mining and Analysis" recently published by Cambridge Press (available online as a free download for personal use).