Item card
Algorithms and data structures.
Some basic information about the module
Cycle of education:
2019/2020
The name of the faculty organization unit:
The faculty Mathematics and Applied Physics
The name of the field of study:
Engineering and data analysis
The area of study:
sciences
The profile of studing:
The level of study:
first degree study
Type of study:
full time
discipline specialities :
The degree after graduating from university:
engineer
The name of the module department :
Department of Electrical and Computer Fundamentals
The code of the module:
12317
The module status:
mandatory for teaching programme
The position in the studies teaching programme:
sem: 1 / W15 L15 P15 / 4 ECTS / Z
The language of the lecture:
Polish
The name of the coordinator:
Grzegorz Drałus, PhD, Eng.
office hours of the coordinator:
http://pei.prz.edu.pl/plan_zajec_semestr.php
semester 1:
Antoni Szczepański, PhD, Eng. , office hours http://pei.prz.edu.pl/plan_zajec_semestr.php
semester 1:
Tomasz Kossowski, PhD, Eng. , office hours http://pei.prz.edu.pl/plan_zajec_semestr.php
semester 1:
Mariusz Borkowski, PhD, Eng.
The aim of studying and bibliography
The main aim of study:
Acquiring knowledge and skills in the field of static and dynamic data structures, selected algorithm construction techniques and computational complexity.
The general information about the module:
Acquiring knowledge and skills in the field of static and dynamic data structures, selected algorithm construction techniques and computational complexity. The module presents basic data structures (lists, stacks, queues, trees) and algorithms for processing these structures with regard to complexity.
Bibliography required to complete the module
| 1 | Cormen T. H., Leiserson C. E., Rivest R. L., Stein C. | Wprowadzenie do algorytmów | Wydawnictwo Naukowe PWN. | 2018 |
| 2 | Wirth Niklauth | Algorytmy + struktury danych = programy | Warszawa, WNT. | 2001. |
| 3 | Wróblewski Piotr | Algorytmy, struktury danych i techniki programowania | Helion. | 2009 |
| 1 | Świder Krzysztof | Wykłady z algorytmów i struktur danych z zadaniami | Oficyna Wydawnicza PRz. | 2004 |
| 2 | Alfred V. Aho, John E. Hopcroft, Jeffrey D. Ullman | Projektowanie i analiza algorytmów | Helion. | 2003 |
| 1 | A.V. Aho,J.E. Hopcroft, J.D. Ullman | Algorytmy i struktury danych | Helion. | 2003 |
| 2 | Sysło Maciej | Algorytmy | Helion. | 2016 |
Basic requirements in category knowledge/skills/social competences
Formal requirements:
The student satisfies the formal requirements set out in the study regulations.
Basic requirements in category knowledge:
The basis of knowledge in computer science, algebra and statistics.
Basic requirements in category skills:
Desired knowledge of any programming language.
Basic requirements in category social competences:
Knowledge and observance of the student's duties and basic ethical principles.
Module outcomes
| MEK | The student who completed the module | Types of classes / teaching methods leading to achieving a given outcome of teaching | Methods of verifying every mentioned outcome of teaching | Relationships with KEK | Relationships with PRK |
|---|---|---|---|---|---|
| MEK01 | Has basic knowledge of selected algorithm design techniques and understands how to improve their efficiency and transparency. | Lecture / Laboratory / Project | Completion part written |
K-W05+ K-W06++ K-U05+ K-K01+ |
P6S-KK P6S-UW P6S-WG |
| MEK02 | Has basic knowledge of elementary data structures (e.g. queue and stack lists, trees) and is able to perform basic operations on these structures. | Lecture / Laboratory / Project | Completion part written. Credit, practical part |
K-W07+ K-U15+ K-U18+ K-K05+ |
P6S-KO P6S-UW P6S-WG |
| MEK03 | Has basic knowledge of sorting algorithms, can explain their operation and assess the complexity of selected algorithms. | Lecture / Laboratory / Project. | Completion part written Completion part practical |
K-W06++ K-W07+ K-U10+ K-U23+ K-K02+ |
P6S-KK P6S-KO P6S-UK P6S-UW P6S-WG |
The syllabus of the module
| Sem. | TK | The content | realized in | MEK |
|---|---|---|---|---|
| 1 | TK01 | W01, W02 | MEK01 | |
| 1 | TK02 | W03, W04 | MEK02 | |
| 1 | TK03 | W05 | MEK01 | |
| 1 | TK04 | W06 | MEK02 | |
| 1 | TK05 | W07 | MEK03 | |
| 1 | TK06 | W08 | MEK01 MEK03 |
The student's effort
| The type of classes | The work before classes | The participation in classes | The work after classes |
|---|---|---|---|
| Lecture (sem. 1) | The preparation for a test:
10.00 hours/sem. |
contact hours:
15.00 hours/sem. |
complementing/reading through notes:
10.00 hours/sem. Studying the recommended bibliography: 10.00 hours/sem. |
| Laboratory (sem. 1) | The preparation for a Laboratory:
7.00 hours/sem. The preparation for a test: 3.00 hours/sem. |
contact hours:
15.00 hours/sem. |
Finishing/Making the report:
7.00 hours/sem. |
| Project/Seminar (sem. 1) | The preparation for projects/seminars:
3.00 hours/sem. |
contact hours:
15.00 hours/sem.. |
Doing the project/report/ Keeping records:
5.00 hours/sem. The preparation for the presentation: 2.00 hours/sem. |
| Advice (sem. 1) | The preparation for Advice:
1.00 hours/sem. |
The participation in Advice:
1.00 hours/sem. |
|
| Credit (sem. 1) | The preparation for a Credit:
7.00 hours/sem. |
The written credit:
2.00 hours/sem. |
The way of giving the component module grades and the final grade
| The type of classes | The way of giving the final grade |
|---|---|
| Lecture | grade from written test. |
| Laboratory | assessment of reports and tasks performed in class. |
| Project/Seminar | assessment of the implementation of the project task. |
| The final grade |
Sample problems
Required during the exam/when receiving the credit
(-)
Realized during classes/laboratories/projects
(-)
Others
(-)
Can a student use any teaching aids during the exam/when receiving the credit : no
The contents of the module are associated with the research profile yes
| 1 | G. Drałus; G. Karnas; G. Masłowski | Identification of cloud-to-ground lightning and intra-cloud lightning based on their radiated electric field signatures using different types of neural networks and machine learning classifiers | 2024 |
| 2 | G. Drałus; J. Kusznier; D. Mazur; K. Szostek | Analysis of the Effectiveness of ARIMA, SARIMA, and SVR Models in Time Series Forecasting: A Case Study of Wind Farm Energy Production | 2024 |
| 3 | G. Drałus; M. Gołębiowski; P. Hawro; P. Krutys; T. Kwater | Comprehensive online estimation of object signals for a control system with an adaptive approach and incomplete measurements | 2024 |
| 4 | G. Drałus | Metody śledzenia punktu MPP modułu fotowoltaicznego | 2023 |
| 5 | G. Drałus; J. Drałus; J. Kusznier; D. Mazur | Application of Artificial Intelligence Algorithms in Multilayer Perceptron and Elman Networks to Predict Photovoltaic Power Plant Generation | 2023 |
| 6 | A. Czmil; G. Drałus; D. Mazur | Automatic Detection and Counting of Blood Cells in Smear Images Using RetinaNet | 2021 |
| 7 | G. Dec; G. Drałus; B. Kwiatkowski; D. Mazur | Forecasting Models of Daily Energy Generation by PV Panels Using Fuzzy Logic | 2021 |
| 8 | G. Drałus; T. Rak | Prognozowanie w horyzoncie jednej godziny produkcji energii przez panel fotowoltaiczny | 2020 |
| 9 | G. Drałus; T. Rak | Programowanie równoległe w hybrydowym środowisku MPI i OpenMP na klastrze serwerów | 2020 |