INTRODUCTION TO CODING

Academic year
2026/2027 Syllabus of previous years
Official course title
DATA, INFORMATION AND SOCIETY 1: INTRODUCTION TO CODING
Course code
ECC082 (AF:765444 AR:454297)
Modality
On campus classes
ECTS credits
6
Degree level
Corso Ordinario Primo Livello
Academic Discipline
SECS-P/01
Period
1st Semester
Course year
1
Where
VENEZIA
Moodle
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The course will introduce the R programming language, starting at a basic level and applying it to data related to Digital Humanities, particularly in cultural studies, economics, and the social sciences. The course will introduce the steps involved in conducting data analysis, depending on whether the data are numerical, textual, or graphical. The theoretical aspects underlying the analytical tools will be explained and then applied using R. The course will therefore highlight how programming can be used in practice in the humanities and social sciences.
Students will be able to use R to critically analyse data relating to topics in the humanities and social sciences, including texts, images, and numerical values. Using the same language, students will be able to create reports illustrating their analyses and results.
No prerequisites are required.
Introduction to algorithms
- Introduction to data analysis
- Main vector types
- Lists
- Data.frame, functions, data import and export
- Loops and iterations
- data.table and merging
- Data visualization
- An illustrative data analysis
- Reports and presentations with RMarkdown
Various readings (articles, blog posts, e-learning resources) provided during the course.
Additional texts (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
Assessment consists of a mid-course test (20% of the final grade) and an R project to be presented at the end of the course (70%). The remaining 10% of the grade will depend on class participation and homework.
written and oral

The instructor is responsible for ensuring the authenticity and originality of all examinations and coursework. In cases of suspected academic misconduct, an additional on-site assessment may be required during the exams, which may differ from the standard format.

The final assessment will consider the accuracy of the analysis, proficiency in R, and clarity of presentation. Grades of 18–23 indicate satisfactory or fair preparation; 24–27 indicate good preparation; 28–30 indicate excellent preparation. Honours will be awarded for exceptional independence and critical thinking.
The course will consist of lectures explaining how the programming language works and discussing its use and applications with students.
Definitive programme.
Last update of the programme: 05/10/2026