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Data Structures and AlgorithmsLaajuus (5 cr)

Code: 4_EFA8030

Credits

5 op

Teaching language

  • English

Learning objectives

Student understands the importance of algorithms and can analyse asymptotic time complextity of simple algorithms.
Student can select and reason correct data structure (abstract data type) for an application and use the chosen structure efficiently.
Student can use efficiently the standard library of his/hers programming language.
Student knows and can implement most common abstract data types, list, tree, and set.
Student can design and implement an algorithm for a simple problem.
Student can search, select, and apply proper algorithm from literature for given problem.
Student knows the principle of recursion and can implement a recursive algorithm.

Content

Algorithms and running time analysis.
Abstract data types.
Implementing data structures.
Searching and sorting algorithms.
Simple recursive algorithms.

Materials

Lecture notes. Any book on data structures and algorithms.

Qualifications

Basics of Programming 1, Basics of Programming 2

Enrollment

01.12.2024 - 15.01.2025

Timing

01.01.2025 - 31.07.2025

Credits

5 op

Mode of delivery

Contact teaching

Teaching languages
  • English
Degree programmes
  • Degree Programme in Internet of Things
Teachers
  • Ville Berg
Student groups
  • IT23SP
    Information Technology IOT

Teaching methods

In this course you will learn basic of data structures and algorihits.

Techings will be hybrid-teachings which means that you can choose to participate remotely if needed. There are about 4 hours of teaching per week for from the beginning of course until independent study week.

Course is passed by doing weekly tasks and participating in course exam(s).

Alternative implementation methods

Exam in exam system

Student workload

Lectures 40 hours, 8 hours to exams and about 80 hours of independent studying

Qualifications

Basics of Programming 1, Basics of Programming 2

Materials

Lecture notes. Any book on data structures and algorithms. For example
Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein: Introduction to Algorithms, 3rd Ed. The MIT Press, 2009

Further information

Course is part of degree programme in Internet of Things.

Enrollment

01.12.2023 - 15.01.2024

Timing

08.01.2024 - 30.04.2024

Credits

5 op

Mode of delivery

Contact teaching

Teaching languages
  • English
Teachers
  • Ville Berg
Student groups
  • EF22SP
    Bachelor Degree Programme in Information Technology IOT

Teaching methods

In this course you will learn basic of data structures and alforihits.

Techings will be hybrid-teachings which means that you can choose to participate remotely if needed. There are about 4 hours of teaching per week for from the beginning of course until independent study week.

Course is passed by doing weekly tasks and participating in courses exams.

Alternative implementation methods

Exam in exam system

Student workload

Lectures 40 hours, 8 hours to exams and about 80 hours of independent studying

Qualifications

Basics of Programming 1, Basics of Programming 2

Materials

Lecture notes. Any book on data structures and algorithms. For example
Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein: Introduction to Algorithms, 3rd Ed. The MIT Press, 2009

Further information

Course is part of degree programme in Internet of Things.

Enrollment

01.12.2022 - 15.01.2023

Timing

01.01.2023 - 30.05.2023

Credits

5 op

Mode of delivery

Contact teaching

Teaching languages
  • English
Teachers
  • Ville Berg
Student groups
  • EF21SP
    Bachelor Degree Programme in Information Technology IOT

Teaching methods

In this course you will learn basic of data structures and alforihits.

Techings will be hybrid-teachings which means that you can choose to participate remotely if needed. There are about 4 hours of teaching per week for from the beginning of course until independent study week.

Course is passed by doing weekly tasks and participating in two middle exams.

Alternative implementation methods

Exam

Student workload

Lectures 40 hours, 8 hours to exams and about 80 hours of independent studying

Qualifications

Basics of Programming 1, Basics of Programming 2

Materials

Lecture notes. Any book on data structures and algorithms. For example
Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein: Introduction to Algorithms, 3rd Ed. The MIT Press, 2009