Data Structures and Algorithms with Python (5 ECTS)

Learning outcomes

After completing the course, student has ability to make comparisons about which data structure and/or algorithm is good for certain programming tasks. She/he has gained ability to use data structures and algorithms in her/his programming.

Content

- Python data types and structures (A Python brief summary)
- Algorithm performance basics and arrays
- Lists
- Stacks and queues
- Trees
- Hashing
- Graphs
- Priority queues and heaps, searching
- Sorting
- Algorithms' design techniques

Teaching methods

Course is 100% online (self-study) course which can be done in own pace.

Location and time

Course environment is Metropolia's Moodle environment and course can be done in own pace.

Learning materials and recommended literature

Online.

Alternative completion methods of implementation

N/A

Internship and working life connections

N/A

Exam dates and retake possibilities

Online in course pace.

International connections

N/A

Student workload

Depends on the student's starting level.

Content scheduling

Up to student her-/himself.

Assessment methods and criteria

Pass after all of tasks and Final has been approved.

Evaluation scale

Hyväksytty/Hylätty

Assessment criteria, satisfactory (1)

- Passed Exam