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Main
UQU Programs
Data Science

Knowledge Representation and Inference

DS2203
3 hours English

Knowledge Representation and Inference

Knowledge Representation and Inference
DS2201 Introduction to Database
3 hours No requisites
1 Introduction to Knowledge Representation
2 Propositional and Predicate Logic
3 Semantic Networks and Frames
4 Ontologies
5 Rule-Based Systems
6 Probabilistic Reasoning and Bayesian Networks
7 Advanced Topics and Applications
8 Review, quizzes and midterm
1.1 Mapped to: K3

Explain key concepts and methods of knowledge representation and their importance in AI and data science.

Teaching Strategy Lectures Discussions
Assessment Methods Exams
1.2 Mapped to: K2

Describe various inference techniques, including logical reasoning, rule-based systems, and probabilistic inference.

Teaching Strategy Lectures Labs
Assessment Methods Exams Assignment
1.3 Mapped to: K1

Understand the limitations and challenges of representing complex knowledge and reasoning in uncertain domains.

Teaching Strategy Discussions Case Studies Project
Assessment Methods Exams Participation Project
2.1 Mapped to: S4

Use formal logic, semantic networks, and ontologies to represent knowledge in structured formats.

Teaching Strategy Labs Case Studies Project
Assessment Methods Exams Assignment Project
2.2 Mapped to: S1

Apply inference techniques, such as resolution and probabilistic reasoning, to derive conclusions from data.

Teaching Strategy Lectures Labs
Assessment Methods Exams Assignment
2.3 Mapped to: S3

Implement knowledge-based systems and reasoning algorithms using programming languages such as OWL or Prolog.

Teaching Strategy Case Studies Project
Assessment Methods Exams Project
3.1 Mapped to: V1

Appreciate the role of structured knowledge in enabling intelligent decision-making systems.

Teaching Strategy Labs Discussions Case Studies
Assessment Methods Exams Participation Assignment
3.2 Mapped to: V2

Recognize the ethical considerations in automating reasoning and decision-making processes.

Teaching Strategy Discussions
Assessment Methods Exams Participation
3.3 Mapped to: V3

Commit to the development of fair, transparent, and responsible knowledge-based systems.

Teaching Strategy Case Studies Project
Assessment Methods Exams Assignment Project
Assessment
Weight
Participation
5%
Lab
10%
Project
15%
Assignments
10%
Midterm exam
20%
Final exam
40%
Total
100%