Computer Programming

(Course Code: 410Υ, Course outline)

Semester: 2 Teaching Credits: 4 ECTS Credits: 5 Type: Compulsory
Prerequisite Courses:  – Course type: General background Instructor: Theodorou Κοnstantinos / Andreou Antonis

The familiarization with the main programming and data analysis methods. The student uses the programming language R, which is an open-source, dynamic script language, powerful in data analysis and statistics. Presentations and lab work are focused on solving problems related to the analysis of environmental data.

Topics per Week: Lectures

  1. Introduction: computer structure, software, algorithms.
  2. Overview of the computer language R.
  3. Data types and basic operations.
  4. Complex data structures.
  5. Subsetting data.
  6. Data input and output; working with files.
  7. Data representation: Graphics with R.
  8. Control structures: conditional.
  9. Control structures: loops.
  10. Control structures in R: the apply family.
  11. Vectorization and optimization.
  12. Functions.
Theory – Lectures
(hours / week):		  3
Exercises – Laboratories
(hours / week):		  3
Other Activities:  –
Grading: Lab work (20%)

Three mid-term exams (30%)

Final exam (50%)
Notes: Presentations and lab notes in pdf form.
Basic Textbook:
  • Φουσκάκης Δ. Ανάλυση δεδομένων με χρήση της R. Εκδόσεις Τσότρας, ISBN: 978‐618‐80741-5-6.
  • Τσιώτας Κ. Γ. Ανάλυση Δεδομένων-Πιθανότητες-Επαγωγή-Εισαγωγή στο R, Εκδόσεις Τζιόλα, ISBN: 978-960-418-578-8.
Bibliography:
  • Matloff (2011). The Art of R Programming
  •  R. I. Kabacoff (2011). R in Action
Language:

Greek
Internet Links:

http://www.cyclismo.org/tutorial/R/

http://www.statmethods.net/