Data Structures and Algorithms Project (5 cr)
Code: TX00EX66-3002
General information
- Enrollment
-
02.12.2024 - 14.01.2025
Registration for the implementation has ended.
- Timing
-
13.01.2025 - 16.03.2025
Implementation has ended.
- Number of ECTS credits allocated
- 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
- Teachers
- Jarkko Vuori
- Groups
-
ICT23-GGame Development
-
tivivaihto_k25Tivi-vaihto, kevät 2025
- Course
- TX00EX66
Implementation has 16 reservations. Total duration of reservations is 48 h 0 min.
| Time | Topic | Location |
|---|---|---|
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Mon 13.01.2025 time 13:00 - 16:00 (3 h 0 min) |
Data Structures and Algorithms Project TX00EX66-3002 |
KME761
Oppimistila
|
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Tue 14.01.2025 time 13:00 - 16:00 (3 h 0 min) |
Data Structures and Algorithms Project TX00EX66-3002 |
KME761
Oppimistila
|
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Mon 20.01.2025 time 13:00 - 16:00 (3 h 0 min) |
Data Structures and Algorithms Project TX00EX66-3002 |
KME761
Oppimistila
|
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Tue 21.01.2025 time 13:00 - 16:00 (3 h 0 min) |
Data Structures and Algorithms Project TX00EX66-3002 |
KME761
Oppimistila
|
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Mon 27.01.2025 time 13:00 - 16:00 (3 h 0 min) |
Data Structures and Algorithms Project TX00EX66-3002 |
KME761
Oppimistila
|
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Tue 28.01.2025 time 13:00 - 16:00 (3 h 0 min) |
Data Structures and Algorithms Project TX00EX66-3002 |
KME761
Oppimistila
|
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Mon 03.02.2025 time 13:00 - 16:00 (3 h 0 min) |
Data Structures and Algorithms Project TX00EX66-3002 |
KME761
Oppimistila
|
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Tue 04.02.2025 time 13:00 - 16:00 (3 h 0 min) |
Data Structures and Algorithms Project TX00EX66-3002 |
KME761
Oppimistila
|
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Mon 10.02.2025 time 13:00 - 16:00 (3 h 0 min) |
Data Structures and Algorithms Project TX00EX66-3002 |
KME761
Oppimistila
|
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Tue 11.02.2025 time 13:00 - 16:00 (3 h 0 min) |
Data Structures and Algorithms Project TX00EX66-3002 |
KME761
Oppimistila
|
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Mon 24.02.2025 time 13:00 - 16:00 (3 h 0 min) |
Data Structures and Algorithms Project TX00EX66-3002 |
KME761
Oppimistila
|
|
Tue 25.02.2025 time 13:00 - 16:00 (3 h 0 min) |
Data Structures and Algorithms Project TX00EX66-3002 |
KME761
Oppimistila
|
|
Mon 03.03.2025 time 13:00 - 16:00 (3 h 0 min) |
Data Structures and Algorithms Project TX00EX66-3002 |
KME761
Oppimistila
|
|
Tue 04.03.2025 time 13:00 - 16:00 (3 h 0 min) |
Data Structures and Algorithms Project TX00EX66-3002 |
KME761
Oppimistila
|
|
Mon 10.03.2025 time 13:00 - 16:00 (3 h 0 min) |
Data Structures and Algorithms Project TX00EX66-3002 |
KME761
Oppimistila
|
|
Tue 11.03.2025 time 13:00 - 16:00 (3 h 0 min) |
Data Structures and Algorithms Project TX00EX66-3002 |
KME761
Oppimistila
|
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.
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