Artificial Intelligence

University of Queensland

Course Description

  • Course Name

    Artificial Intelligence

  • Host University

    University of Queensland

  • Location

    Brisbane, Australia

  • Area of Study

    Information Technologies

  • Language Level

    Taught In English

  • Prerequisites

    CSSE1001

  • Course Level Recommendations

    Upper

    ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.

    Hours & Credits

  • Host University Units

    2
  • Recommended U.S. Semester Credits
    4
  • Recommended U.S. Quarter Units
    6
  • Overview

    Course Description
    Methods & techniques within the field of artificial intelligence, including problem solving and optimisation by search, representing and reasoning with uncertain knowledge and machine learning. Specific emphasis on the practical utility of algorithms and their implementation in software.
     
     
    Learning Objectives
    After successfully completing this course you should be able to:
    1. Able to explain the theories, methods and practices which form the basis of artificial intelligence.
    2. Able to critically read text material and extract useful knowledge applicable to the specific course contents.
    3. Effectively solve problems relating to topics discussed in class and in the literature.
    4. Implement artificial intelligence techniques using high level programming language.
    5. Effectively frame real-world problems into problems solvable by existing techniques in artificial intelligence.
     
    Class Contact
    2 Lecture hours, 2 Tutorial hours
     
     
    Assessment
    Taking notes
    Type: Handout
    Learning Objectives Assessed: 2
    Due Date: Throughout Semester
    Weight: 5%
    Task Description: Each student is required to take lecture notes of half a lecture (i.e., around 50 min lecture), and distribute the notes to the entire class via the class forum, at most 3 days after the lecture. Details on who should take the notes when will be available at the class website
     
     
    Assignment 1
    Type: Project
    Learning Objectives Assessed: 2, 3, 4, 5
    Due Date:Early Semester
    Weight: 15%
    Assignments are intended to test:
    • Students understanding of the material discussed in lectures and tutorials.
    • Students ability in framing a simplified real-world problem into a problem solvable by existing artificial intelligence techniques.
    • Students ability in choosing an appropriate artificial intelligence technique to solve a problem.
    • Students ability to implement artificial intelligence techniques using high-level programming language.
    • Students ability to convey their solution in a manner accessible by their peers.
     
     
    Assignment 2
    Type: Project
    Learning Objectives Assessed: 2, 3, 4, 5
    Due Date: Mid-Semester
    Weight: 15%
    Assignments are intended to test:
    • Students understanding of the material discussed in lectures and tutorials.
    • Students ability in framing a simplified real-world problem into a problem solvable by existing artificial intelligence techniques.
    • Students ability in choosing an appropriate artificial intelligence technique to solve a problem.
    • Students ability to implement artificial intelligence techniques using high-level programming language.
    • Students ability to convey their solution in a manner accessible by their peers
     
     
    Mid term exam
    Type: Exam - Mid Semester During Class
    Learning Objectives Assessed: 1, 2
    Due Date:Mid Semester
    Weight: 15%
    Reading: 5 minutes
    Duration: 55 minutes
    Format: Short answer, Short essay
    Task Description: The quiz will be in-class and closed-book. This quiz will cover only part 1 of the class (including Assignment 1).
     
     
    Assignment 3
    Type: Project
    Learning Objectives Assessed: 2, 3, 4, 5
    Due Date: Mid Semester
    Weight: 15%
    Assignments are intended to test:
    • Students understanding of the material discussed in lectures and tutorials.
    • Students ability in framing a simplified real-world problem into a problem solvable by existing artificial intelligence techniques.
    • Students ability in choosing an appropriate artificial intelligence technique to solve a problem.
    • Students ability to implement artificial intelligence techniques using high-level programming language.
    • Students ability to convey their solution in a manner accessible by their peers.
     
     
    Final Exam
    Type: Exam - during Exam Period (Central)
    Learning Objectives Assessed: 1, 2, 3, 4, 5
    Due Date: Examination Period
    Weight: 35%
    Reading: 10 minutes
    Duration: 120 minutes
    Format: Short essay, Extended essay, Problem solving
    Task Description: Final exam will cover all parts of the course, including assignments.

Course Disclaimer

Courses and course hours of instruction are subject to change.

Eligibility for courses may be subject to a placement exam and/or pre-requisites.

Some courses may require additional fees.

Credits earned vary according to the policies of the students' home institutions. According to ISA policy and possible visa requirements, students must maintain full-time enrollment status, as determined by their home institutions, for the duration of the program.