INF2420 - Introduction to Data Science

It is a capital mistake to theorize before one has data.
Sherlock Holmes in “A Study in Scarlett” (Arthur Conan Doyle).

Suggested References: 

- Laura Igual, and Santi Seguí. "Introduction to Data Science”, Springer, Cham, 2017.

- Larry Wasserman. All of statistics: a concise course in statistical inference. Springer Science & Business Media, 2013.

- Nina Zumel and John Mount. Practical Data Science with R, Manning, 2014.

- Crhistopher Gandrud, Reproducible Research with R and RStudio, R Series, CRC Press, 2014.

- Yihui Xie, Dynamic Documents with R and Knitr, R Series, CRC Press, 2014.

- Oscar P. Lamigueiro, Displaying Time Series, Spatial and Space-Time Data with R, R Series, CRC Press, 2014.

- Gareth James et al., An Introduction to Statistical Learning with Application in R, Springer, 2013.

- Eric D. Kolasky and Gabor Csárdi, Statistical Analysis of Network Data with R, Springer, 2014.

Software:

http://www.anaconda.com/

http://www.r-project.org/

http://www.rstudio.com/

DataCamp-Vertical-CMYK


This class is supported by DataCamp, the most intuitive learning platform for data science and analytics. Learn any time, anywhere and become an expert in R, Python, SQL, and more. DataCamp’s learn-by-doing methodology combines short expert videos and hands-on-the-keyboard exercises to help learners retain knowledge. DataCamp offers 325+ courses by expert instructors on topics such as importing data, data visualization, and machine learning. They’re constantly expanding their curriculum to keep up with the latest technology trends and to provide the best learning experience for all skill levels. Join over 5 million learners around the world and close your skills gap.

e-mail: lopes at inf dot puc-rio dot br
Tel: 55+21+3527-1500 R:4350  Fax: 55+21+3527-1530
Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio) - Departamento de Informática - Sala 408 RDC
Rua Marquês de São Vicente 225, Gávea, Rio de Janeiro, RJ, Brazil, CEP 22451-900