Introduction to Computer Science II

Μάθημα: Introduction to Computer Science II
Course Number: B0041
Ώρα:
Προαπαιτούμενα:
Μονάδες: 5
Αίθουσα:
Ημέρα:
Component(s):
Χάρτης: Map

COURSE OUTLINE

  1. GENERAL
SCHOOL AGRICULTURAL AND FORESTRY SCIENCES
DEPARTMENT AGRICULTURAL DEVELOPMENT
LEVEL OF STUDIES 7
COURSE CODE B0041 SEMESTER 1st, 3d, 5th
COURSE TITLE INTRODUTION IN COMPUTER SCIENCE II
TEACHING ACTIVITIES
If the ECTS Credits are distributed in distinct parts of the course e.g. lectures, labs etc. If the ECTS Credits are awarded to the whole course, then please indicate the teaching hours per week and the corresponding ECTS Credits.		 TEACHING HOURS PER WEEK ECTS CREDITS
Lectures and laboratory exercises  (3+2) 5
 
 
Please, add lines if necessary. Teaching methods and organization of the course are described in section 4.
COURSE TYPE

Background, General Knowledge, Scientific Area, Skill Development

 Core/Optional
PREREQUISITES:

 

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TEACHING & EXAMINATION LANGUAGE: Greek
COURSE OFFERED TO ERASMUS STUDENTS: No
COURSE URL: https://eclass.duth.gr/courses/GEO104/
  1. LEARNING OUTCOMES
Learning Outcomes
Please describe the learning outcomes of the course: Knowledge, skills and abilities acquired after the successful completion of the course.
Upon the completion of the course the students;

·        become acquainted with R package.

·        Should be capable of Mathematical Processing at available data

·        Should be capable of Statistical processing at available data.
General Skills
Name the desirable general skills upon successful completion of the module
Search, analysis and synthesis of data and information,

ICT Use

Adaptation to new situations

Decision making

Autonomous work

Teamwork

Working in an international environment

Working in an interdisciplinary environment

Production of new research ideas

 Project design and management

Equity and Inclusion

Respect for the natural environment

Sustainability

Demonstration of social, professional and moral responsibility and sensitivity to gender issues

Critical thinking

Promoting free, creative and inductive reasoning
  • Analytical and Synthetical Thinking

·        Knowledge on Mathematics
  1. COURSE CONTENT
·        Introduction

·         Calculations

·        Functions

·        Data

·        Iteration and Testing commands

·        Specific Commands

·        Data processing

·        Γραφικές παραστάσεις/ Διαγράμματα στην R:

·        Simulation

·        Inference Statistics

·        Descriptive Statistics

·        Linear Regression

·         Variance Analysis
  1. LEARNING & TEACHING METHODS – EVALUATION
TEACHING METHOD
Face to face, Distance learning, etc.		 Face to face, Distance Learning via Microsoft Teams Platform
USE OF INFORMATION & COMMUNICATIONS TECHNOLOGY (ICT)
Use of ICT in Teaching, in Laboratory Education, in Communication with students		 Power Point,

Communication via email and eclass platform
TEACHING ORGANIZATION

The ways and methods of teaching are described in detail.

Lectures, Seminars, Laboratory Exercise, Field Exercise, Bibliographic research & analysis, Tutoring, Internship (Placement), Clinical Exercise, Art Workshop, Interactive learning, Study visits, Study / creation, project, creation, project. Etc.

 

The supervised and unsupervised workload per activity is indicated here, so that total workload per semester complies to ECTS standards.
Activity Workload/semester
Activity Semester workload
Lectures 39
Exercises 26
Individual study 60
Course total 125
(25-hour workload per credit unit)  
Student Evaluation

Description of the evaluation process

 

Assessment Language, Assessment Methods, Formative or Concluding, Multiple Choice Test, Short Answer Questions, Essay Development Questions, Problem Solving, Written Assignment, Essay / Report, Oral Exam, Presentation in audience, Laboratory Report, Clinical examination of a patient, Artistic interpretation, Other/Others

 

Please indicate all relevant information about the course assessment and how students are informed 

Written exams at the end of the semester both on theory and computer lab

Two tests are taken within the semester and the average of the grade of those tests is multiplied by 0,3 and is added to the grade of the final test. The precondition for the validity of this bonus is the grade of the final test to be equal or over three. 2. Assignments are delegated to the students that are graded with ranking 0-2. The grade of this assignment is added to the final grade of the semester The precondition for the validity of this bonus is the grade of the final test to be equal or over three

 

 
  1. SUGGESTED BIBLIOGRAPHY
§  33134029]: Data analysis with R, Fouskakis D. (in Greek)

§  [22767853]: Matlab in Computers and Science, Charles F. Van Loan & K-Y Daisy Fan (in Greek)

§   [59397371]: Apllications of Mathematick in Agriculture, Koutroumanidis Th., Zafeiriou E., Malesios Ch. (in Greek)

 

 

 

 

 

 

ANNEX OF THE COURSE OUTLINE

 

Alternative ways of examining a course in emergency situations

 

Teacher (full name):
Contact details:
Supervisors: (1) Yes
Evaluation methods: (2) Oral Exams with distance methods
Implementation Instructions: (3) The examination will be realized in group of 5 students. The group will change every 20 minutes based on a name list. The exam will be realized via  SKYPE FOR BUSINESS. On the link you will be notified through eclass on your institutional accounts. The connection to the link is possible only through the student institutional account. The camera during the exam should be on. Prior to the examination an identification is needed. Every student should response to 4 questions with each one of the to be graded with 2.5 out of 10.