INTRODUCTION TO CODING

Academic year
2022/2023 Syllabus of previous years
Official course title
DATA, INFORMATION AND SOCIETY 1: INTRODUCTION TO CODING
Course code
ECC082 (AF:435050 AR:239823)
Modality
On campus classes
ECTS credits
6
Degree level
Corso Ordinario Primo Livello
Educational sector code
INF/01
Period
1st Semester
Course year
1
Where
VENEZIA
Moodle
Go to Moodle page
The course will introduce the use of the R programming language, starting from a basic level and applying it to data related to Digital Humanities studies, in particular from cultural studies, from sociology and anthropology. During the course, the various steps to follow to develop a data analysis project will be presented, by making use of numerical data, text data, or graphical data. Theoretical aspects related to the functioning of the tools that are part of these steps will be explained and applied through the use of the R language. The course will highlight how programming might be fruitfully applied in Social Sciences and Digital Humanities research.
The students will be able to use the R programming language to critically analyze data related to Digital Humanities and Social Sciences, such as numerical data, text data and image data. At the end of the course, the students will be able to use R to perform quantitative data analysis and create reports presenting it.
There are no prerequisites.
- Introduction to Algorithms
- Intro to Data Analysis
- Main Vector Types
- Lists
- Data frames, Functions, Data Import and Export
- Loops and Iteration
- data.table and Merging
- Data Visualisation
- An illustrative Data Analysis
- Reporting Using Markdown
- Geospatial Data (maps)
Selected articles will be proposed during the course, and shared on Moodle

Additional books and manuals (optional):
H. Wickham and G. Grolemund, “R for data science”, O’Reilly Media, 2016 (https://r4ds.had.co.nz )
C. Chapman and E. McDonnell Feit, “R for Marketing Research and Analytics”, Springer, 2015
T. Arnold and L. Tilton, “Humanities data in R. Exploring networks, geospatial data, images, and text” Springer, 2015
The assessment will consist of a test after the first half of the course (20% of the final mark) and in the development of a final project, realized using the R language, to be presented in class (70% of the final mark). Class participation and homework will account for 10% of the final mark.
Frontal lectures. During the course, the R programming language will be presented and then actively used by, and discussed with, the students.
written and oral
Definitive programme.
Last update of the programme: 28/09/2022