ALGORITHMS FOR BIG DATA

Course Information
TitleΑΛΓΟΡΙΘΜΟΙ ΔΕΔΟΜΕΝΩΝ ΜΕΓΑΛΗΣ ΚΛΙΜΑΚΑΣ / ALGORITHMS FOR BIG DATA
CodeNIS-08-05
FacultySciences
SchoolInformatics
Cycle / Level1st / Undergraduate
Teaching PeriodSpring
CoordinatorGeorgios Christodoulou
CommonNo
StatusActive
Course ID600020378

Programme of Study: PPS-Tmīma Plīroforikīs (2019-sīmera)

Registered students: 41
OrientationAttendance TypeSemesterYearECTS
GENIKĪ KATEUTHYNSĪYPOCΗREŌTIKO KATA EPILOGĪ845
Class Information
Academic Year2024 – 2025
Class PeriodSpring
Faculty Instructors
Weekly Hours3
Total Hours39
Class ID
600259874
Course Type 2021
Specific Foundation
Course Type 2016-2020
  • Scientific Area
Course Type 2011-2015
Knowledge Deepening / Consolidation
Mode of Delivery
  • Face to face
Digital Course Content
Language of Instruction
  • Greek (Instruction, Examination)
Prerequisites
General Prerequisites
There are no formal prerequisite courses as this requirement does not exist in the Department of Informatics. However, good knowledge in the subjects Data Structures, Algorithms, Algorithms and Complexity is required.
Learning Outcomes
Knowledge: Training on implementation and advanced techniques for big data management. Acquisition of practical and theoretical knowledge of algorithmic implementation techniques and of advanced data management topics. Skills: Application of advanced data management techniques in modern problems, implementation of efficient data management techniques and experimental evaluation.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Adapt to new situations
  • Make decisions
  • Work autonomously
  • Work in teams
  • Advance free, creative and causative thinking
Course Content (Syllabus)
Mathematical background Approximate and randomized algorithms Sublinear algorithms Algorithms for data streams Online algorithms Optimal termination theory Online learning
Keywords
big data, algorithms, data structures, data streams
Educational Material Types
  • Notes
  • Slide presentations
  • Book
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
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures52✓✓
Reading Assigment30✓✓
Project60✓✓
Written assigments8✓✓
Total150
Student Assessment
Description
Written exams (total weight 60%), project (40%)
Student Assessment methods
  • Written Exam with Short Answer Questions (Formative, Summative)
  • Written Assignment (Formative, Summative)
  • Performance / Staging (Formative, Summative)
  • Written Exam with Problem Solving (Formative, Summative)
  • Report (Formative, Summative)
Bibliography
Course Bibliography (Eudoxus)
ΑΛΓΟΡΙΘΜΟΙ Κωδικός Βιβλίου στον Εύδοξο: 13583 Έκδοση: 1η/2009 Συγγραφείς: SANJOY DASGUPTA, CHRISTOS PAPADIMITRIOU, UMESH VAZIRANI ISBN: 9789604612116 Τύπος: Σύγγραμμα Διαθέτης (Εκδότης): ΕΚΔΟΣΕΙΣ ΚΛΕΙΔΑΡΙΘΜΟΣ ΕΠΕ
Additional bibliography for study
http://repfiles.kallipos.gr/html_books/4410/contents.html A. Borodin and R. El-Yaniv, Online Computation and Competitive Analysis, Cambridge
Last Update
29-03-2023