Data Structures and Algorithms (5 cr)

Evaluation scale

H-5

Content scheduling

- Algorithms and algorithmic thinking
- Data structures
- Search algorithms
- Sorting algorithms

Contact hours according to lukkari.turkuamk.fi.

Objective

After completing the course the student can:
- explain the most common data structures
- apply the most common data structures and algorithms connected to the use of these structures
- evaluate the efficiency of algorithms.

Content

- lists, stacks, queues, trees, graphs and hash tables
- analysing and evaluating algorithms
- designing algorithms
- sorting methods
- search algorithms

Materials

Material available via the learning environment (ITS).

Teaching methods

Weekly contact 3 hours sessions for theory and practical exercises. Project work and project work presentation.

Exam schedules

If your exercise points is less than 50 % of total exercise points you have to do demonstration exam.

Format and dates for exam are decided when number of students participating in the exam is known.

Pedagogic approaches and sustainable development

Course has weekly
- 2h theory sessions that contain small exercises for students
- 1h practice session where students homework is checked and discussed in small groups

Electronic materials are used in the course.

Completion alternatives

Not possible

Student workload

Contact hours
- 14 times 2h theory: 14 x 2h = 28 hours
- 13 times 1h practice 13 x 1h = 13 hours - Group 1
- 13 times 1h practice 13 x 1h = 13 hours - Group 2

Home work:
- Working with assignments: approximately 80 hours
- If you are not present in related practice session your homework is not assessed. To get exercise points you have to do and return assignments in time, be present and participate in group conversation during the practice sessions.


Total: approximately 130 hours

Evaluation methods and criteria

The course is evaluated on a scale of 0-5.

The use of artificial intelligence varies from one learning task to another. Instructions on AI usage are instructed on an assignment-specific basis but use of AI has to be always reported.

Attendance to theory sessions: 20 %
Exercises are 40 % of the grade
Project work 40 % of the grade
Project work presentation is either pass/failed where failed means that you didn't do it.

To get exercise points you have to do and return assignments in time, be present and participate in group conversation during the practice sessions. If your exercise points is less than 50 % of total exercise points you have to do demonstration exam which replaces your exercise points. To pass the exam you need 40% of the total points of the exam. Existing exercise points are taken into account in the assessment of the exam.

Failed (0)

If you have less than 50% of exercise points and did not pass demonstration exam or have less than 50% of the project work points or did not do project work presentation.

Assessment criteria, satisfactory (1-2)

50-69 % of the total points of the course

Assessment criteria, good (3-4)

70-89 % of the total points of the course

Assessment criteria, excellent (5)

over 90 % of the total points of the course

Qualifications

Introduction to Programming, or equivalent programming skills

Further information

ITS e-mail.