DATA SCIENCE
| Title | ΕΠΙΣΤΗΜΗ ΔΕΔΟΜΕΝΩΝ / DATA SCIENCE |
| Code | APBC.01.01 |
| Faculty | Sciences |
| School | Biology |
| Cycle / Level | 2nd / Postgraduate |
| Teaching Period | Winter/Spring |
| Coordinator | Spyridon Papakostas |
| Common | No |
| Status | Active |
| Course ID | 600022120 |
Programme of Study: DIPMS EFARMOSMENĪ VIOPLĪROFORIKĪ 2022
Registered students: 30
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| KORMOS | Compulsory Course | 1 | 1 | 6 |
| Academic Year | 2025 – 2026 |
| Class Period | Winter |
| Faculty Instructors | |
| Instructors from Other Categories |
|
| Weekly Hours | 11 |
| Total Hours | 33 |
| Class ID | 600289739
|
Course Type 2021
Specific Foundation
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600289739
- eLearning (Moodle): https://elearning.auth.gr/course/view.php?id=17263
Language of Instruction
- English (Instruction, Examination)
Learning Outcomes
Upon successful completion of the course, students will:
1) learn the basic programming structures in the python and R languages
2) be able to process and visualize large-scale data
3) learn the fundamentals of data mining and machine learning
4) become familiar with cloud computing and the use of supercomputers
5) be able to work in a UNIX/Linux environment.
General Competences
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
Course Content (Syllabus)
The course contents include: 1) learning python, 2) learning R, 3) data processing and visualization, 4) basic principles of statistical analysis, 5) basic principles of data mining and machine learning, 6) cloud computing and use of supercomputers (learning UNIX/Linux). Emphasis in learning the above will be placed on biological data using specific examples and exercises.
Educational Material Types
- Slide presentations
- Video lectures
- Interactive excersises
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Laboratory Teaching
- Use of ICT in Communication with Students
- Use of ICT in Student Assessment
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 96 | 3.8 | |||
| Laboratory Work | 16 | 0.6 | |||
| Interactive Teaching in Information Center | 12 | 0.5 | |||
| Exams | 26 | 1.0 | |||
| Total | 150 | 6 |
Student Assessment
Student Assessment methods
- Written Exam with Multiple Choice Questions (Summative)
- Written Exam with Short Answer Questions (Summative)
- Written Exam with Problem Solving (Summative)
- Report (Summative)
Last Update
28-01-2024
