Algorithms and Data StructuresLaajuus (5 cr)
Code: R504D75
Credits
5 op
Objective
The student knows and can apply the primary data structures and algorithms. The student can compare their efficiency and complexity.
Content
- Algorithmic complexity and evaluation of the performance of algorithms: the Big O notation.
- The primary data structures and their implementations: arrays, linked lists, stacks, queues, graphs, binary trees.
- The primary algorithms and their implementations: recursion, searching and sorting.
Assessment criteria, satisfactory (1)
The student can compare the complexity of algorithms and apply some basic data structures and algorithms.
Assessment criteria, good (3)
The student can compare the complexity of algorithms and apply a variety of data structures and algorithms. The student is familiar with the internal implementation of the most common data structures and algorithms.
Assessment criteria, excellent (5)
The student can evaluate the complexity of algorithms and apply a wide variety of data structures and algorithms. The students is familiar with the internal implementation of the primary data structures and algorithms. The student can choose the most effective data structures and algorithms for a given task.
Enrollment
18.03.2024 - 31.07.2024
Timing
05.09.2024 - 31.10.2024
Credits
5 op
Mode of delivery
Contact teaching
Unit
Bachelor of Engineering, Information Technology
Teaching languages
- English
Seats
0 - 30
Degree programmes
- Machine Learning and Data Engineering
Teachers
- Erkki Mattila
Responsible person
Erkki Mattila
Student groups
-
R54D22S
Objective
The student knows and can apply the primary data structures and algorithms. The student can compare their efficiency and complexity.
Content
- Algorithmic complexity and evaluation of the performance of algorithms: the Big O notation.
- The primary data structures and their implementations: arrays, linked lists, stacks, queues, graphs, binary trees.
- The primary algorithms and their implementations: recursion, searching and sorting.
Location and time
Computer labs at Rantavitikka Campus in the autumn term 2024.
Materials
Lecture materials, examples, exercises and assignments in Moodle workspace and/or OneDrive.
Course book
Carrano F. & Henry T. 2018. Data Structures and Abstractions with Java. 5th Edition. Pearson
Recommended reading
Goodrich M. T. & al. 2014. Data Structures and Algorithms in Java: International Student Version. 6th Edition.
Wiley Weiss M. 2012. Data Structures and Algorithm Analysis in Java: International Edition. 3rd Edition. Pearson Education
Teaching methods
Lectures and exercises, assignment and self-supervised work.
Evaluation scale
H-5
Assessment criteria, satisfactory (1)
The student can compare the complexity of algorithms and apply some basic data structures and algorithms.
Assessment criteria, good (3)
The student can compare the complexity of algorithms and apply a variety of data structures and algorithms. The student is familiar with the internal implementation of the most common data structures and algorithms.
Assessment criteria, excellent (5)
The student can evaluate the complexity of algorithms and apply a wide variety of data structures and algorithms. The students is familiar with the internal implementation of the primary data structures and algorithms. The student can choose the most effective data structures and algorithms for a given task.