Course finder

  • Arts and Audiences 2 (AHE4032)

    Start: Period 4

    Faculty of Arts and Social Sciences

    Course

    Arts and Audiences 2

  • Calculus (KEN1440)

    Start: Period 4

    Data Science & Knowledge Engineering

    Course
  • Computer Security (KEN2560)

    Start: Period 1

    Data Science & Knowledge Engineering

    Course
  • Culture and Economy 2 (AHE4031)

    Start: Period 4

    Faculty of Arts and Social Sciences

    Course

    Culture and Economy 2

  • Data Analysis (KEN3450)

    Start: Period 4

    Data Science & Knowledge Engineering

    Course
  • Data Structures and Algorithms (KEN1420)

    Start: Period 4

    Data Science & Knowledge Engineering

    Course
  • Databases (KEN2110)

    Start: Period 1

    Data Science & Knowledge Engineering

    Course
  • Discrete Mathematics (KEN1130)

    Start: Period 1

    Data Science & Knowledge Engineering

    Course
  • Game Theory (KEN3130)

    Start: Period 1

    Data Science & Knowledge Engineering

    Course
  • Graph Theory (KEN2220)

    Start: Period 2

    Data Science & Knowledge Engineering

    Course
  • Heritage and Society 2 (AHE4033)

    Start: Period 4

    Faculty of Arts and Social Sciences

    Course

    Heritage and Society 2

  • Human Computer Interaction & Affective Computing (KEN2410)

    Start: Period 4

    Data Science & Knowledge Engineering

    Course
  • Intelligent Systems (KEN3430)

    Start: Period 4

    Data Science & Knowledge Engineering

    Course
  • Internship (AHE4992)

    Start: Period 4

    Faculty of Arts and Social Sciences

    Internship

    Internship

  • Introduction to Bio-Informatics (KEN3440)

    Start: Period 2

    Data Science & Knowledge Engineering

    Course

    Introduction to Bio-Informatics introduces the student to the fundamental methods and techniques of bioinformatics in biomedical and biological research. The main objective of the course is that the student acquires a general understanding of bioinformatics methods at the algorithmic level. This will enable the student to read and understand publications in this field, and apply their knowledge in concrete biological problems. The major areas and problems in bioinformatics will be discussed, such as sequence alignment, phylogenetic analysis, gene finding and gene expression analysis. The lectures and computer lectures in this course will be based on relevant real case-studies that highlight the main topics in the course. After completing this course the student has obtained a general understanding of bioinformatics methods at the algorithmic level. The student will be able to understand the major problems in bioinformatics and how their knowledge can be applied to such problems.