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CIT474Sciences2 Unitsintermediate

Introduction to Expert Systems

This course introduces the fundamental concepts of expert systems, a branch of artificial intelligence. It covers the components, development, and applications of expert systems across various domains. Students will learn about knowledge representation techniques, including rule-based, frame-based, and fuzzy logic systems. The course also explores neural network-based expert systems and their applications, equipping students with the skills to design and implement intelligent systems.

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40h
Study Time
13
Weeks
3h
Per Week
basic
Math Level
Course Keywords
Expert SystemsArtificial IntelligenceKnowledge RepresentationInference EngineRule-Based Systems

Course Overview

Everything you need to know about this course

Course Difficulty

Intermediate Level
Builds on foundational knowledge
65%
intermediate
➕
Math Level
Basic Math
📖
Learning Type
Theoretical Focus

Course Topics

Key areas covered in this course

1

Introduction to Expert Systems

2

Components of Expert Systems

3

Knowledge Representation

4

Rule-Based Systems

5

Frame-Based Systems

6

Fuzzy Logic and Neural Networks

7

Blackboard Systems

8

Expert System Shells

9

Current Trends in Expert Systems

Total Topics9 topics

Requirements

Knowledge and skills recommended for success

Basic programming skills

Familiarity with data structures

Introduction to Artificial Intelligence

💡 Don't have all requirements? Don't worry! Many students successfully complete this course with basic preparation and dedication.

Assessment Methods

How your progress will be evaluated (3 methods)

assignments

Comprehensive evaluation of course material understanding

Written Assessment

tutor-marked assignments

Comprehensive evaluation of course material understanding

Written Assessment

final examination

Comprehensive evaluation of course material understanding

Written Assessment

Career Opportunities

Explore the career paths this course opens up for you

AI Developer

Apply your skills in this growing field

Knowledge Engineer

Apply your skills in this growing field

System Analyst

Apply your skills in this growing field

Data Scientist

Apply your skills in this growing field

Software Engineer

Apply your skills in this growing field

Industry Applications

Real-world sectors where you can apply your knowledge

HealthcareFinanceManufacturingAerospaceTelecommunications

Study Schedule Beta

A structured 13-week journey through the course content

Week
1

Module 1: Basic Concept of Expert Systems

2h

Unit 1: Introduction to Expert Systems

2 study hours
  • •Understand the historical background of expert systems.
  • •Define an expert system and its key features.
  • •Identify the roles of individuals involved in expert system development.
  • •List the advantages and disadvantages of expert systems.
Week
2

Module 1: Basic Concept of Expert Systems

2h

Unit 2: Components of Expert Systems, and Development of an Expert System

2 study hours
  • •Discuss the components of an expert system: user interface, inference engine, knowledge base, working memory, and explanation facility.
  • •Understand how expert systems operate.
  • •Explain the steps involved in developing an expert system.
Week
3

Module 1: Basic Concept of Expert Systems

2h

Unit 3: The Need for Expert Systems and Applications

2 study hours
  • •Discuss the need for expert systems in various organizations.
  • •Identify factors that make an expert system appropriate for a given problem.
  • •Explore the application areas of expert systems, including accounting, finance, agriculture, and medicine.
Week
4

Module 1: Basic Concept of Expert Systems

2h

Unit 4: Knowledge Representation in Expert Systems

2 study hours
  • •Discuss knowledge representation in expert systems.
  • •Explain different types of knowledge representation methods, such as production rules, semantic nets, and frames.
  • •Analyze the benefits and disadvantages of each knowledge representation method.
Week
5

Module 2: Classes of Expert System

2h

Unit 1: A rule-based expert system

2 study hours
  • •Explain rule-based systems and their characteristics.
  • •Study the example of Mycin, a rule-based expert system.
  • •Analyze the components of Mycin and its history.
  • •Discuss the advantages and disadvantages of rule-based systems.
Week
6

Module 2: Classes of Expert System

2h

Unit 2: Frame-based expert system

2 study hours
  • •Understand the concept of frame-based expert systems.
  • •Define terms associated with frame-based systems, such as frames, slots, and attributes.
  • •Explain how demons are triggered in frame-based systems.
Week
7

Module 2: Classes of Expert System

2h

Unit 3: Fuzzy and neural network based expert system

2 study hours
  • •Understand fuzzy logic-based expert systems.
  • •Understand neural network-based expert systems.
  • •Discuss the advantages and disadvantages of each type of system.
Week
8

Module 2: Classes of Expert System

2h

Unit 4: Blackboard Expert System – HEARSAY

2 study hours
  • •Define a blackboard system and its components.
  • •Identify the components of the Hearsay expert system.
  • •Discuss the benefits of blackboard architecture.
Week
9

Module 2: Classes of Expert System

2h

Unit 5: Expert System Shells

2 study hours
  • •Understand how to select an expert system for an organization.
  • •Know the criteria for selecting an expert system.
  • •Discuss the factors to consider when choosing an expert system-based tool.
Week
10

Module 2: Classes of Expert System

2h

Unit 5: Expert System Shells

2 study hours
  • •Define expert system shells.
  • •Explain the components of a shell, including the knowledge base, reasoning engine, knowledge acquisition subsystem, explanation subsystem, and user interface.
Week
11

Module 3: Current trends in expert systems.

2h

Unit 1: New development in expert systems

2 study hours
  • •Discuss the current trends in expert systems.
  • •Understand the industries with wide expert system applications.
  • •Explore new developments in expert systems, such as machine learning and data mining.
Week
12

Module 3: Current trends in expert systems.

3h

Final Revision

3 study hours
  • •Review all modules and units.
  • •Focus on key concepts and definitions.
  • •Practice problem-solving techniques.
Week
13

Module 3: Current trends in expert systems.

3h

Final Revision

3 study hours
  • •Complete assignments and prepare for the final examination.
  • •Review tutor-marked assignments and feedback.
  • •Consolidate understanding of course materials.

This study schedule is in beta and may not be accurate. Please use it as a guide and consult the course outline for the most accurate information.

Course PDF Material

Read the complete course material as provided by NOUN.

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Study Tips & Exam Preparation

Expert tips to help you succeed in this course

1

Review all lecture notes and study materials thoroughly.

2

Practice solving problems and case studies from the course.

3

Focus on understanding the key concepts and definitions.

4

Create concept maps linking different modules and units.

5

Practice with expert system development tools like CLIPS or JESS.

6

Review all tutor-marked assignments and feedback.

7

Allocate time for revision and practice questions in the last two weeks.

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