Information Theory - ANU Programs and Courses. Programs and Courses Search query Search ANU web, staff & maps Search current site content Search Programs and Courses Courses COMP2610 Course Information Theory An undergraduate course offered by the School of Computing. COMP2610 Academic Year 2021 2022 2021 2020 2019 2018 2017 2016 2015 2014 Code COMP2610 Unit Value 6 units Academic Codes Offered by School of Computing ANU College ANU College of Engineering and Computer Science Course subject Computer Science Academic career UGRD Course convener Prof Thushara Abhayapala Mode of delivery In Person Co-taught Course COMP6261 Offered in Second Semester 2021 See Future Offerings Tweet Share on Facebook Wattle Share SELT Survey Results Overview Study Fees Class Code COMP2610 Unit Value 6 units Offered by School of Computing ANU College ANU College of Engineering and Computer Science Course subject Computer Science Academic career UGRD Course convener Prof Thushara Abhayapala Mode of delivery In Person Co-taught Course COMP6261 Offered in Second Semester 2021 See Future Offerings Tweet Share on Facebook Wattle Share SELT Survey Results Information Theory (COMP2610) Introduction Learning Outcomes Indicative Assessment Workload Requisite and Incompatibility Prescribed Texts Assumed Knowledge Majors Fees Offerings and Dates Course has been adjusted for remote participation in 2021. Some on-campus activities are available. Attendance at these where possible is encouraged. Information theory studies the fundamental limits of the representation and transmission of information. This course provides an introduction to information theory, studying fundamental concepts such as probability, information, and entropy and examining their applications in the areas of data compression, coding, communications, pattern recognition and probabilistic inference. Learning Outcomes Upon successful completion, students will have the knowledge and skills to: Upon successful completion of the course, the student will have background knowledge necessary to understand problems in data compression, storing and communication and undertake advanced courses on statistical inference, machine learning and information engineering. In particular, the student will be able to: Understand and apply fundamental concepts in information theory such as probability, entropy, information content and their inter-relationships. Understand the principles of data compression. Compute entropy and mutual information of random variables. Implement and analyse basic coding and compression algorithms. Understand the relationship of information theoretical principles and Bayesian inference in data modelling and pattern recognition. Understand some key theorems and inequalities that quantify essential limitations on compression, communication and inference. Know the basic concepts regarding communications over noisy channels. Indicative Assessment Assignment 1 (10%) Assignment 2 (20%) Assignment 3 (20%) Final Exam (50%) The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website. Workload Twenty-six one-hour lectures and five two-hour tutorial sessions. Requisite and Incompatibility You cannot enrol in this course if you have completed COMP6261 or ENGN8534. Prescribed Texts Information Theory, Inference, and Learning Algorithms by David MacKay, Cambridge University Press, 2003. Additional reading: Elements of Information Theory by Cover and Thomas, 2nd Edition, New York, Wiley, 2006. Assumed Knowledge Some background in elementary statistics and probability. Majors Digital Humanities Fees Tuition fees are for the academic year indicated at the top of the page. Commonwealth Support (CSP) Students If you have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). More information about your student contribution amount for each course at Fees. Student Contribution Band: 2 Unit value: 6 units If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees. Where there is a unit range displayed for this course, not all unit options below may be available. Units EFTSL 6.00 0.12500 Course fees Domestic International Domestic fee paying students Year Fee 2021 $4410 International fee paying students Year Fee 2021 $5880 Note: Please note that fee information is for current year only. Offerings, Dates and Class Summary Links The list of offerings for future years is indicative only. Class summaries, if available, can be accessed by clicking on the View link for the relevant class number. 2021 2022 Second Semester Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary 5442 26 Jul 2021 02 Aug 2021 14 Sep 2021 29 Oct 2021 In Person N/A Second Semester Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary 5407 25 Jul 2022 01 Aug 2022 31 Aug 2022 28 Oct 2022 In Person N/A Responsible Officer: Registrar, Student Administration / Page Contact: Website Administrator / Frequently Asked Questions Contact ANU Campus Map Copyright Disclaimer Privacy Freedom of Information +61 2 6125 5111 The Australian National University, Canberra CRICOS Provider : 00120C ABN : 52 234 063 906
