Information Package
baskent.edu.tr

Master's of Computer Engineering with Thesis

BİL584

KNOWLEDGE MANAGEMENT AND ENGINEERING

Course Code
BİL584
Semester
-
Theory+Practice
3 + 0
ECTS
10
Course TypeElective Course
Course LevelMaster's Degree With Thesis
Year of Study-
Semester-
ECTS10
Name of Lecturer(s) -
Learning Outcomes

At the end of this course, the students;

  1. Will have a better understanding of knowledge and knowledge types.
  2. Will learn Knowledge Management (KM) and various issues related to this topic.
  3. Will learn Knowledge Engineering (KE) and its relation to Knowledge Management.
  4. Will have a better understanding of Knowledge Management & Engineering (KME) Technologies: Artificial Intelligence (AI), Knowledge Based Systems (KBS) and Knowledge Modeling.
  5. Will learn KME Systems Life Cycle.
Mode of DeliveryFace to face
PrerequisitesNo
Recommended Optional Programme ComponentsNone
Course DescriptionIntroduction: Knowledge, Knowledge Society, eEurope Project. The Nature of Knowledge and Knowledge Types. Knowledge Management - General, Principles, KM Solutions. Knowledge Engineering. Knowledge Management and Engineering (KME) Technologies. KME Technologies: AI and KBS. Case Based Reasoning Systems (CBRS) and Data Mining. Knowledge Modeling - DFD. Knowledge Modeling - UML. KME Systems Life Cycle. The Future of KME.
Course Contents
WEEK TOPICS
1st Week Introduction: Knowledge, Knowledge Society, eEurope Project.
2nd Week The Nature of Knowledge and Knowledge Types.
3rd Week Knowledge Management - General.
4th Week Knowledge Management - Principles.
5th Week Knowledge Management - KM Solutions.
6th Week Knowledge Engineering.
7th Week Knowledge Management and Engineering (KME) Technologies.
8th Week Mid-term
9th Week KME Technologies - AI and KBS.
10th Week KME Technologies - Case Based Reasoning Systems (CBRS) and Data Mining.
11th Week KME Technologies - Knowledge Modeling - DFD.
12th Week KME Technologies - Knowledge Modeling - UML.
13th Week KME Systems Life Cycle.
14th Week The Future of KME.
Recommended or Required ReadingCourse Book: Becerra-Fernandez, I. A. Gonzalez, and R. Sabherwal "Knowledge Management", Pearson / Prentice Hall, 2004.
References:
1. Rhem, A.J. "UML for Developing Knowledge Management Systems", Auerbaclı, 2006.
2. Tiwana, A. "The Knowledge Management Toolkit", Pearson / Prentice Hall, 2002.
3. Awad, E.M. and H.M.Ghaziri , "Knowledge Management", Prentice Hall, 2004.
Planned Learning Activities and Teaching Methods
  • Presentation
Assessment Methods and Criteria
Quantity Percentage (%)
Mid-term 1 30
Assignment 1 5
Quiz 1 15
Project 1 10
Total(%) 60
Contribution of In-term Studies to Overall Grade(%) 60
Contribution of Final Examination to Overall Grade(%) 40
Total(%) 100
ECTS Allocated Based on Student Workload
Activities Quantity Duration (Hour) Total Workload (Hour)
Midterm exam 1 2 2
Preparation for Quiz
Individual or group work 14 11 154
Preparation for Final exam 1 69 69
Course hours 14 3 42
Preparation for Midterm exam 1 44 44
Laboratory (including preparation)
Final exam 1 2 2
Homework
Total Work Load313
Total Work Load / 30 (h)10.43
ECTS Credit of the Course10
Language of InstructionTurkish
Work Placement(s)No

Programme Qualifications / Learning Outcomes

LO1 LO2 LO3 LO4 LO5
K1 X X X X
K2 X X X X X
K3 X X X X X
K4 X X X X X
K5 X X X X X
K6 X
K7 X
K8 X X X X X
K9 X
K10 X
K11 X
K12 X