ΣΥΝΕΔΡΙΟ EUROGEO - 2022: 5-6 ΜΑΪΟΥ 2022

COURSE OUTLINE



(1) General

School:Social Sciences
Academic Unit:Geography
Level of studies:Undergraduate
Course Code:GEO 441Semester:E
Course Title:Introduction to computer programming
Independent Teaching ActivitiesWeekly Teaching HoursCredits
Lecture2
Laboratory practice2
Course total5
Course Type:Required Elective
Prerequisite Courses:
Language of Instruction and ExaminationsGreek
Is the course offered to Erasmus students:No
Course Website (Url):https://geography.aegean.gr/pps/index_en.php?content=0&lesson=441


(2) Learning Outcomes

Learning Outcomes

Upon completion of the course the student is expected to:

  • List the basic programming instructions
  • Analyze a computational problem in subproblems and procedures/functions
  • Design an algorithm using a logic diagram
  • Describe and use the data structures supported by a programming language
  • Write code into a computer programming language
  • Apply Object Oriented Programming methodology
  • Use classes and methods for geographic data calculations
  • Respond to the challenges of implementing new geographic data calculations

General Competences

  1. Search for, analysis and synthesis of data and information, with the use of the necessary technology

  2. Working independently

  3. Project planning and management

  4. Production of free, creative and inductive thinking


(3) Syllabus

Teaching modules:

  • Software Engineering - Algorithms - Programs
  • Basic programming language elements
  • Programming using decision instructions
  • Programming using looping instructions
  • Procedures
  • Data Structures
  • Object-Oriented Programming - Classes - Objects
  • Calculations for geographic data I
  • Calculations for geographic data II
  • Calculations for geographic data III
  • Calculations for geographic data IV
  • Calculations for geographic data V

(4) Teaching and Learning Methods - Evaluation

Delivery:
Face-to-face.
Use of Information and Communication Technology:
Diagrams drawing applications - R programming language / R Studio
Teaching Methods:
ActivitySemester workload
Lecture26
Laboratory practice26
Project40
Non-supervised study39
Performance evaluation/Exams3
Course total134
Student Performance Evaluation
Individual assignments (4) - Laboratory examination - Written examination


(5) Attached Bibliography

  • Introduction to Programming and Statistical Analysis with R, D. Karlis - I. Djoufras, Hellenic Academic eBooks (kallipos.gr) (in Greek)
  • Data science through the R language, V. S. Verkyios - V. Kaglis - H. K. Stavropoulos, Hellenic Academic eBooks (kallipos.gr) (in Greek)
  • Lecture Notes by the instructor (in Greek).