Data Structures and Algorithms Project (5 cr)
Code: TX00EX66-3004
General information
- Enrollment
-
27.11.2023 - 14.01.2024
Registration for the implementation has ended.
- Timing
-
15.01.2024 - 17.03.2024
Implementation has ended.
- Number of ECTS credits allocated
- 5 cr
- Local portion
- 5 cr
- Mode of delivery
- On-campus
- Unit
- (2019-2024) School of ICT
- Campus
- Karaportti 2
- Teaching languages
- English
- Seats
- 0 - 35
- Degree programmes
- Degree Programme in Information Technology
Implementation has 11 reservations. Total duration of reservations is 29 h 0 min.
| Time | Topic | Location |
|---|---|---|
|
Wed 17.01.2024 time 13:00 - 16:00 (3 h 0 min) |
Data Structures and Algorithms Project TX00EX66-3004 |
KME559
Oppimistila
|
|
Mon 22.01.2024 time 09:00 - 11:30 (2 h 30 min) |
Data Structures and Algorithms Project TX00EX66-3004 |
Online
|
|
Wed 24.01.2024 time 13:00 - 16:00 (3 h 0 min) |
Data Structures and Algorithms Project TX00EX66-3004 |
KMD750
Oppimistila
|
|
Mon 29.01.2024 time 09:00 - 12:00 (3 h 0 min) |
Data Structures and Algorithms Project TX00EX66-3004 |
Online
|
|
Wed 31.01.2024 time 13:00 - 16:00 (3 h 0 min) |
Data Structures and Algorithms Project TX00EX66-3004 |
KME559
Oppimistila
|
|
Wed 07.02.2024 time 13:00 - 16:00 (3 h 0 min) |
Data Structures and Algorithms Project TX00EX66-3004 |
KME559
Oppimistila
|
|
Mon 12.02.2024 time 09:30 - 12:00 (2 h 30 min) |
Data Structures and Algorithms Project TX00EX66-3004 |
KMD659
Oppimistila
|
|
Wed 14.02.2024 time 13:00 - 16:00 (3 h 0 min) |
Data Structures and Algorithms Project TX00EX66-3004 |
KME559
Oppimistila
|
|
Mon 26.02.2024 time 09:30 - 12:00 (2 h 30 min) |
Data Structures and Algorithms Project TX00EX66-3004 |
KMD659
Oppimistila
|
|
Mon 04.03.2024 time 09:30 - 12:00 (2 h 30 min) |
Data Structures and Algorithms Project TX00EX66-3004 |
KMD659
Oppimistila
|
|
Mon 11.03.2024 time 09:30 - 10:30 (1 h 0 min) |
Data Structures and Algorithms Project TX00EX66-3004 |
Online
|
Objective
Student is able to implement a project requiring design and implementation of non-trivial data structures and algorithms. He/she is able to analyze and compare different algorithmic solutions, in terms of memory and time requirements. He/she is is able to utilize classis AI algorithms.
Content
- data structures
- algorithms
- project planning and implementation
- time and space requirements
- AI algorithms
Evaluation scale
0-5
Assessment criteria, satisfactory (1)
Student has achieved the course objectives fairly. Student will be able to identify, define and use the course subject area’s concepts and models. Student understands the criteria and principles of the expertise development.
Assessment criteria, good (3)
Student has achieved the course objectives well, even though the knowledge and skills need improvement on some areas. Student is able to define the course concepts and models and is able to justify the analysis. Student is able to apply his/her knowledge in study and work situations. Student understands the importance of expertise in the field of information and communication technology and is able to analyze his/her own expertise.
Assessment criteria, excellent (5)
Student has achieved the objectives of the course with excellent marks. Student masters commendably the course subject area’s concepts and models. Student is able to make justified and fluent analysis and to present concrete development measures. Student is well prepared to apply his/her knowledge in study and work situations. Student is able to analyze expertise in the information and communication technology sector and the development of his/her own expertise.
Assessment criteria, approved/failed
Student has achieved the course objectives fairly. Student will be able to identify, define and use the course subject area’s concepts and models. Student understands the criteria and principles of the expertise development.