Study Guide

Objective

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

Location and time

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

Materials

Online.

Teaching methods

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

Employer connections

N/A

Exam schedules

Online in course pace.

International connections

N/A

Completion alternatives

N/A

Student workload

Depends on the student's starting level.

Content scheduling

Up to student her-/himself.

Evaluation scale

Hyväksytty/Hylätty

Assessment criteria, satisfactory (1)

- Passed Exam

Assessment methods and criteria

Pass after all of tasks and Final has been approved.