Data Structures and Algorithms (5 cr)

Evaluation scale

H-5

Content scheduling

Understanding data structures and algorithmic efficiency / complexity are essential in many ways. During this course, the student will gain both theoretical and practical understanding on these topics. Students will learn to use pseudocode / flowcharts to describe algorithms and analyze their complexity (time and space, both experimental and theoretical). We will gain a comprehensive insight to elementary data structures and their algorithms.

Practical understanding is gained through coding exercises. We will use Python as our main coding language.

January– April 2025

January and February: Algorithms and algorithmic thinking
• pseudocode, flowcharts
• efficiency and algorithmic complexity
• Sorting algorithms: Bubble, Selection, Insertion, Merge and Quick Sort

March and April: Data Structures and their algorithms
• Arrays, Linked List, Stack, Queue
• Hash table, Trees, Graphs

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

Lecture and practice session material in ItsLearning, e.g. PowerPoint presentations, Jupyter notebook / Python files, etc.
All material is provided in English

Teaching methods

Attending to lectures: teacher will provide both theoretical background and practical examples on a dedicated topic
Attending practice sessions: the theory is put into action in practice - we will see solutions to previous exercises + practice new topics
Individual work: Completing the assignments individually after face-to-face sessions

Exam schedules

No exam, retake not possible after the publication of the final assessment/course grade

International connections

The course has 14 two-hour contact sessions where teacher present theory and examples, and 12 two-hour practice sessions where students work with practical tasks.

Electronic materials are used in the course.

Completion alternatives

Ask teacher, if there is an ongoing suitable online course (FiTech / Coursera or equivalent).
CampusOnline courses ARE NOT accepted!

Student workload

Lectures 2h / week x 14 = 28h
Practice sessions 2h x 12 = 24h
Individual work outside school: reading, studying, preparing the weekly programming practice tasks: 80h

Total: approx. 80h

Qualifications

Introduction to Programming, or equivalent programming skills

Further information

ItsLearning
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