Course Title: Artificial Intelligence Concepts and Applications

Part A: Course Overview

Course Title: Artificial Intelligence Concepts and Applications

Credit Points: 12.00

Course Code




Learning Mode

Teaching Period(s)


City Campus


140H Computer Science & Information Technology


Sem 1 2006


City Campus


140H Computer Science & Information Technology


Sem 1 2006

Course Coordinator: Vacant

Course Coordinator Phone: +61 3 9925 2348

Course Coordinator Email:

Pre-requisite Courses and Assumed Knowledge and Capabilities

This course is aimed at students who are interested in fundamental concepts in Artificial Intelligence areas but do not necessarily have a strong computer science background. To successfully complete this course, some familiarity with programming and basic data structures is required. Familiarity with Unix is strongly recommended. Completion of one of these courses would satisfy the pre-requisite requirements: Java for Programmers or Programming 2 or Java for C Programmers.

Course Description

Note: This course is not currently available. There are no plans to reintroduce it in the near future, as well.

This course aims to introduce you to the fundamental concepts of artificial intelligence and some practical techniques, with examples implemented using a variety of software tools. The focus is on basic methodology and the tasks that can be accomplished with these tools, rather than on a deep understanding of the underlying algorithms. You will have a brief overview of the field of Artificial Intelligence without going deep into the theoretical aspects. You will also learn the fundamental concepts of some AI systems such as game, expert system, chatterbot, fuzzy logic, machine learning and neural networks via using existing software.

Objectives/Learning Outcomes/Capability Development

You will gain capabilities in:

• General overview of the area of artificial intelligence.
• Use a variety of artificial intelligence software tools which will include games, natural language processors, expert systems, fuzzy logic inference systems, data mining tools and neural networks.
• Understanding of the techniques used in these tools.
• Critical analysis and problem solving: you will analyze variety problems and select an appropriate technique for solve these problems.

On successful completion of this course, you will be able to:

• Describe an artificial intelligence system in terms of its basic methodology and structure.
• Analyze a practical problem and formalize it into a task which might be able to be solved by one of the known AI techniques.
• Select and recommend one or a set of appropriate AI techniques to address a particular practical problem.
• Assess the accuracy or performance of various AI techniques on a particular task.
• Describe the advantages, disadvantages and related issues of a AI technique on a particular task.

Overview of Learning Activities

The learning activities included in this course are:

• key concepts will be explained in lectures, seminars or online, where syllabus material will be presented and the subject will be illustrated with demonstrations and examples;
• tutorials, laboratory exercises and group discussions (including online forums) focussed on problem solving will provide practice in the application of theory and procedures, allow exploration of concepts with tutors and other students, and give feedback on your progress and understanding;
• written assignments consisting of numerical and other problems requiring an integrated understanding of the subject matter; and
• private study, working through the course as presented in classes and learning materials, and gaining practice at solving conceptual and numerical problems.

Overview of Learning Resources

You will be able to access course information and learning materials through the Learning Hub (also known as online@RMIT) and will be provided with copies of additional materials in class or via email. Lists of relevant reference texts, resources in the library and freely accessible Internet sites will be provided.

Overview of Assessment

The assessment for this course comprises assignments during the semester, and an examination at the end of the semester. The assignments during the semester will demonstrate your capabilities in critical analysis, problem solving and operational procedures to successfully complete several tasks by using the AI tools introduced during the semester. The examination at the end of the semester will demonstrate your knowledge of the key concepts of the tools, your ability to analyse problems and your ability to select an appropriate techniques to problem solving.

For standard assessment details, including deadlines, weightings, and hurdle requirements relating to Computer Science and IT courses see: