Data Processing
BASIC DATA
course listing
A - main register
course code
IDK1615
course title in Estonian
Andmetöötlus
course title in English
Data Processing
course volume CP
-
ECTS credits
6.00
to be declared
yes
fully online course
not
assessment form
Examination
teaching semester
autumn - spring
language of instruction
Estonian
English
Study programmes that contain the course
code of the study programme version
course compulsory
EAXM15/25
no
IABB17/25
yes
TAAB02/25
yes
TABB02/25
yes
display more
Structural units teaching the course
IT - Department of Software Science
Course description link
Timetable link
View the timetable
Version:
VERSION SPECIFIC DATA
course aims in Estonian
Anda baasteadmised ja oskused kontoritarkvara kasutamisest andmete töötlemiseks ja analüüsiks. Anda oskused programmeerimisvahendite kasutamisest andmete töötlemiseks. Andmete statistiline töötlemine.
course aims in English
To provide basic knowledge and skills for using office software for processing and analyzing data. To provide skills using programming tools for processing data. Statistical data processing.
learning outcomes in the course in Est.
Tudeng oskab:
1. Tunneb tõenäosusteooria põhitermineid, tunneb matemaatilise statistika põhitermineid, oskab leida punkt- ja vahemikhinnanguid; teab mitmesuguseid jaotusfunktsioone.
2. Kasutada programmi MS Excel statistiliste andmete töötlemiseks.
3. Luua kontoritarkvara abil rakendusi, mis sisaldavad tabelarvutust, tekstitöötlust ja esitluste loomist.
4. Kasutada infootsinguid andmete leidmiseks ja importimiseks veebilehtedelt ja andmebaasidest.
5. Automatiseerida korduvaid tegevusi, kujundada kasutajaliidest ja kasutada muid kontoritarkvara programmeerimisvõimalusi.
6. Leida lahendusi algoritmilist mõtlemisviisi kasutades.
7. Integreerida kontoritarkvara lahendusi heli-, pildi- ja videotöötlustarkvaraga, jälgides turvalisusega seonduvaid probleeme.
learning outcomes in the course in Eng.
Student is able to:
1. Knows the main concepts of the theory of probability, main concepts of the mathematical statistics, is able to find point and interval estimators; knows the concepts of distribution function.
2. Use MS Excel for processing statistical data.
3. Create software solutions using office software (spreadsheets, word processing, presentations)
4. Use queries to find and import data from web-pages and databases.
5. Record repeating activities, design user interface and use other programming capabilities of office software.
6. Find solutions using algorithmic thinking.
7. Integrate office software solutions with other software (photo, audio, video) following principles of data security.
brief description of the course in Estonian
Ülevaade kontoritarkvarast. Kontortarkvara komponendid - tabelarvutus, tekstitöötlus, esitlustarkvara. Kontoritööks vajalik riistvara, võrguvara ning pilverakenduste ja meeskonnatöö kasutuse võimalus.
Tabelarvutuses kasutatavad funktsioonid kategooriate lõikes.
Andmetabelid. Koondandmete loomisvõimalused andmete analüüsimiseks. Andmete visualiseerimine.
Tõenäosusteooria ja matemaatilise statistika põhimõisted, punkt- ja vahemikhinnangud, jaotusfunktsioonid ning vastavad MS Excel vahendid.
Andmekaitse.
Töökeskkonna häälestamine.
Töö automatiseerimine makrode abil.
Visuaalse-, sündmus- ja objekt-orienteeritud programmeerimise põhimõte.
Kasutajaliidese kujundamine andmepäringuteks ja andmete sisestamiseks.
Programmeerimiskeele VBA baasteadmised.
Andmetabeli objekt-orienteeritud vaade. Objektide omadused, meetodid ja sündmused.
Andmevahetus erinevate kontoritarkvara komponentide ja teiste tarkvarapakettide vahel. Pildi-, heli- ja videovahendite lisamine kontoritarkvara rakendustesse.
Praktilised ülesanded ja kodutööd põhinevad tõenäosusteooria ja matemaatilise statistika ülesannetel.
brief description of the course in English
Overview of office software. Components of office software - spreadsheets, word processing, presentations. Needed hardware and netware for office software, principles of using cloud computing and teamwork.
Categories of functions in spreadsheet systems.
Data tables. Ways to make total tables to analyze data. Data visualization.
Probability theory and mathematical statistics, basic concepts, point and interval estimation, distribution functions and the corresponding MS Excel tools.
Data protection.
Customizing work environment.
Automation tasks using macros.
Principles of visual, event-driven and object-oriented programming.
Designing user interface for data query and data entry.
Basic knowledge of programming language VBA.
Object-oriented view of data sheets. Properties, methods and events of objects.
Data export and import between office software components and other software packages. Integrating photo, audio and video solutions into office applications.
Exercises, practical assignments and homework are based on tasks from probability theory and mathematical statistics domains.
type of assessment in Estonian
Eksam toimub arvutiklassis. Igale üliõpilasele antakse ülesanne, mis tuleb realiseerida kontoritarkvara vahenditega.
Eksami sooritamiseks on aega kolm ja pool tundi. Eksami sooritamiseks tuleb loodud lahenduse tööd demonstreerida eksaminaatori arvutis, selgitada realisatsiooni ning vastata esitatud küsimustele.
Eristav hindamine – eksamitöö annab maksimaalselt 60 punkti.
Kolmveerand punktidest annab ülesande funktsionaalsete nõuete täitmine, veerandi lahenduse ratsionaalsus ja kasutajaliidese kujundus.
Tulemus:
„1“ – kasin eksamitöö lahenduse tase st lahenduse funktsionaalsus toimib vaid umbes pooles ulatuses või lahenduses on tõsiseid vigu, kaitsmisel küsimustele vastamisel esineb olulisi probleeme. Eksamitööga saadakse 51-60% punktidest.
„2“ – rahuldav eksamitöö lahenduse tase st lahenduse funktsionaalsuses on puudusi või lahenduses on tõsiseid vigu, kaitsmisel küsimustele vastamisel esineb mõningaid probleeme. Eksamitööga saadakse 61-70% punktidest.
„3“ – hea eksamitöö lahenduse tase st lahenduse funktsionaalsus on realiseeritud, kuid esineb mõningaid vähemtähtsaid vigu, kaitsmisel küsimustele vastamisel esineb väheseid probleeme. Eksamitööga saadakse 71-80% punktidest.
„4“ – väga hea eksamitöö lahenduse tase st lahenduse funktsionaalsus on realiseeritud, kuid lahenduse ratsionaalsus ja/või kasutajasõbralikkus jätab soovida, kaitsmisel küsimustele vastamisel probleeme ei teki. Eksamitööga saadakse 81-90% punktidest.
„5“ – suurepärane eksamitöö lahenduse tase st lahenduse funktsionaalsus on realiseeritud ratsionaalselt ja kasutajasõbralikult ning kaitsmisküsimustele vastamisel probleeme ei teki. Eksamitööga saadakse 91-100% punktidest.
HINDAMISELE PÄÄSEMISE EELDUSED
Esitatud ja kaitstud on neli iseseisvat tööd. Iga töö eest on võimalik saada maksimaalselt 10 punkti.
LÕPPHINDE KUJUNEMINE
10% Kodutöö (K)1; 10% K2; 10% K3; 10% K4; 60% Eksam (E). Tulemuse arvutamise aluseks on K1, K2, K3, K4 ja E kogutud punktid.
Koondtulemus = K1 + K2 + K3 + K4 + E
Tulemus muudetakse hindeks 0 kuni 5: 0-50 „0“; 51-60 „1“; 61-70 „2“; 71-80 „3“; 81-90 „4“; 91-100 „5“
type of assessment in English
Exam takes place in a computer class. Every student gets an assignment that must be solved with office software tools. The time for solving the assignment is 3.5 hours. To pass the exam, the solutions must be demonstrated on the examinator’s computer, the solution must be explained and questions asked must be answered to.
Marking- the maximum number of points for the exam is 60. 75% of the points are based on the functional requirements of the assignment and 25% on the rationality of the solution and user interface design.
The result is:
„1“ – poor level of exam problem solving, i.e. the solution functions only ~50% or the solution includes significant errors, during defence the student has significant problems answering to the questions. The exam problem gives 51-60% of the points.
„2“ – satisfactory level of exam problem solving, i.e. there exist shortcomings in functionality or the solution includes significant errors, during defence the student has some problems answering to the questions. The exam problem gives 61-70% of the points.
„3“ – good level of exam problem solving, i.e. the functionality has been achieved, but there exist some less significant errors, during defence the student has minor problems answering to the questions. The exam problem gives 71-80% of the points.
„4“ – very good level of exam problem solving, i.e. the functionality has been achieved, but there exist problems in rationality of the solution and/or in its user-friendliness, during defence the student has no problems answering to the questions. The exam problem gives 81-90% of the points.
„5“ – excellent level of exam problem solving, i.e. the functionality has been rationally achieved and is user-friendly, during defence the student has no problems answering to the questions. The exam problem gives 91-100% of the points.
ELIGIBILITY FOR ASSESSMENT
In order to be eligible for the exam four home assignments must have been submitted and defended. Each assignment gives maximum 10 points.
FINAL MARK
10% Homework (HW)1; 10% HW2; 10% HW3; 10% HW4; 60% Exam (E) grading is based on points received for HW1, HW2, HW3, HW4 and E.
Final result =HW1 + HW2 + HW3 + HW4 + E
Result is turned into mark 0 to 5: 0-50 „0“; 51-60 „1“; 61-70 „2“; 71-80 „3“; 81-90 „4“; 91-100 „5“

independent study in Estonian
Tähtaegselt esitatavad, iseseisvalt lahendatavate ülesannetega, mis tuleb õppejõu juures kaitsta. Ülesandeid on kokku neli (K1, K2, K3, K4).
independent study in English
Students are given independent assignments to solve, submitted according to the deadline and defended at the lecturer. There are 4 assignments in total (HW1, HW2, HW3, HW4).
study literature
1. Amitan I., Vilipõld J. MS Excel. Rakenduste loomise põhielemendid. TTÜ, 2001.
2. T. Luczkowski. Excel ja VBA . TTÜ, 2009
3. Listra, E. Äristatistika I. Tallinn: TTÜ, 1998.
4. Aarma, A., Lutsoja, K. Statistika praktikumide ülesandeid. Tallinn: TTÜ, 2004.
study forms and load
daytime study: weekly hours
4.0
session-based study work load (in a semester):
lectures
2.0
lectures
-
practices
2.0
practices
-
exercises
0.0
exercises
-
lecturer in charge
-
LECTURER SYLLABUS INFO
semester of studies
teaching lecturer / unit
language of instruction
Extended syllabus
2025/2026 autumn
Kersti Antoi, IT - Department of Software Science
Estonian
    Julia Ratšinskaja, IT - Department of Software Science
    Estonian
      Ahti Lohk, IT - Department of Software Science
      Estonian
        display more
        2024/2025 spring
        Kersti Antoi, IT - Department of Software Science
        Estonian
          2024/2025 autumn
          Kersti Antoi, IT - Department of Software Science
          Estonian
            Irina Amitan, IT - Department of Software Science
            Estonian
              Ahti Lohk, IT - Department of Software Science
              Estonian
                2023/2024 spring
                Kersti Antoi, IT - Department of Software Science
                Estonian
                  2023/2024 autumn
                  Irina Amitan, IT - Department of Software Science
                  Estonian
                    Ahti Lohk, IT - Department of Software Science
                    Estonian
                      Kersti Antoi, IT - Department of Software Science
                      Estonian
                        2022/2023 spring
                        Kersti Antoi, IT - Department of Software Science
                        Estonian
                          2022/2023 autumn
                          Kersti Antoi, IT - Department of Software Science
                          Estonian
                            Irina Amitan, IT - Department of Software Science
                            Estonian
                              2021/2022 spring
                              Kersti Antoi, IT - Department of Software Science
                              Estonian
                                IDK1615hindamiskriteeriumidENG.pdf 
                                2021/2022 autumn
                                Mart Roost, IT - Department of Software Science
                                Estonian
                                  IDK1615hindamiskriteeriumidENG.pdf 
                                  Irina Amitan, IT - Department of Software Science
                                  Estonian
                                    IDK1615hindamiskriteeriumidENG.pdf 
                                    Kersti Antoi, IT - Department of Software Science
                                    Estonian
                                      IDK1615hindamiskriteeriumidENG.pdf 
                                      2020/2021 spring
                                      Kersti Antoi, IT - Department of Software Science
                                      Estonian
                                        IDK1615hindamiskriteeriumidENG.pdf 
                                        2020/2021 autumn
                                        Kersti Antoi, IT - Department of Software Science
                                        Estonian
                                          IDK1615hindamiskriteeriumidENG.pdf 
                                          Irina Amitan, IT - Department of Software Science
                                          Estonian
                                            IDK1615hindamiskriteeriumidENG.pdf 
                                            2019/2020 spring
                                            Kersti Antoi, IT - Department of Software Science
                                            Estonian
                                              IDK1615hindamiskriteeriumidENG.pdf 
                                              2019/2020 autumn
                                              Irina Amitan, IT - Department of Software Science
                                              Estonian
                                                IDK1615hindamiskriteeriumidENG.pdf 
                                                Kersti Antoi, IT - Department of Software Science
                                                Estonian
                                                  IDK1615hindamiskriteeriumidENG.pdf 
                                                  2018/2019 spring
                                                  Kersti Antoi, IT - Department of Software Science
                                                  Estonian
                                                    IDK1615hindamiskriteeriumidENG.pdf 
                                                    2018/2019 autumn
                                                    Irina Amitan, IT - Department of Software Science
                                                    Estonian
                                                      IDK1615hindamiskriteeriumidENG.pdf 
                                                      Kersti Antoi, IT - Department of Software Science
                                                      Estonian
                                                        IDK1615hindamiskriteeriumidENG.pdf 
                                                        2017/2018 spring
                                                        Teodor Luczkowski, IT - Department of Software Science
                                                        Estonian
                                                          IDK1615hindamiskriteeriumidENG.pdf 
                                                          2017/2018 autumn
                                                          Teodor Luczkowski, IT - Department of Software Science
                                                          Estonian
                                                            IDK1615hindamiskriteeriumidENG.pdf 
                                                            Irina Amitan, IT - Department of Software Science
                                                            Estonian
                                                              IDK1615hindamiskriteeriumidENG.pdf 
                                                              Kersti Antoi, IT - Department of Software Science
                                                              Estonian
                                                                IDK1615hindamiskriteeriumidENG.pdf 
                                                                Course description in Estonian
                                                                Course description in English