Courses & Units
Artificial Intelligence and Natural Language KIT719
Introduction
This unit is designed to give students an insight into a range of natural language processing (NLP) techniques. NLP is a critical step towards effective communication between people and machines. You will learn the basics NLP steps as well as some advanced NLP patterns such as information extraction and text summarisation. This unit includes a number of Artificial Intelligence (AI) areas - classification and clustering, text mining, sentiment analysis, and the use of web technology for NLP application domains (Semantic Web, information retrieval, chatbot).
With the technologies discussed in the lectures, it brings together the state-of-the-art research and practical techniques in NLP, providing students with the knowledge and capacity to conduct NLP research and to develop NLP applications. Students are required to use web application programming interfaces (APIs) and text mining tools to explore and specialise their understanding, and also required to use these technologies to develop a system for a NLP web application.
Summary
| Unit name | Artificial Intelligence and Natural Language |
|---|---|
| Unit code | KIT719 |
| Credit points | 12.5 |
| College/School | College of Sciences and Engineering School of Information and Communication Technology |
| Discipline | Information & Communication Technology |
| Coordinator | Doctor Quan Bai |
| Teaching staff | Doctor Son Tran |
| Delivered By | University of Tasmania |
| Level | Postgraduate |
Availability
| Location | Study period | Attendance options | Available to | ||
|---|---|---|---|---|---|
| Hobart | Semester 1 | On-Campus | International | Domestic | |
| Hobart | Semester 2 | On-Campus | International | Domestic | |
| Launceston | Semester 1 | On-Campus | International | Domestic | |
| Launceston | Semester 2 | On-Campus | International | Domestic | |
Key
- On-campus
- Off-Campus
- International students
- Domestic students
Key Dates
| Study Period | Start date | Census date | WW date | End date |
|---|---|---|---|---|
| Semester 1 | 21/2/2022 | 22/3/2022 | 11/4/2022 | 29/5/2022 |
| Semester 2 | 11/7/2022 | 9/8/2022 | 29/8/2022 | 16/10/2022 |
* The Final WW Date is the final date from which you can withdraw from the unit without academic penalty, however you will still incur a financial liability (refer to How do I withdraw from a unit? for more information).
Unit census dates currently displaying for 2022 are indicative and subject to change. Finalised census dates for 2022 will be available from the 1st October 2021. Note census date cutoff is 11.59pm AEST (AEDT during October to March).
Learning Outcomes
- Describe the principle of NLP processes, methods and the applications of NLP in real applications.
- Explain the linkage between AI and NLP and be able to adopt suitable AI methods which can be embedded in NLP and text mining approaches.
- Adopt methodologies, tools, research skills and techniques for the processing, analysing and mining of natural language data.
- Analyse user needs and incorporate them into the selection, creation, adaption and evaluation of appropriate NLP and text mining methods to support decision making.
Fee Information
| Field of Education | Commencing Student Contribution 1,3 | Grandfathered Student Contribution 1,3 | Approved Pathway Course Student Contribution 2,3 | Domestic Full Fee 4 |
|---|---|---|---|---|
| 020119 | $1,002.00 | $1,002.00 | not applicable | $2,402.00 |
1 Please refer to more information on student contribution amounts.
2 Please refer to more information on eligibility and Approved Pathway courses.
3 Please refer to more information on eligibility for HECS-HELP.
4 Please refer to more information on eligibility for FEE-HELP.
If you have any questions in relation to the fees, please contact UConnect or more information is available on StudyAssist.
Please note: international students should refer to What is an indicative Fee? to get an indicative course cost.
Teaching
| Teaching Pattern | Weekly 2hr lecture Weekly 2hr tutorial |
|---|---|
| Assessment | Test or quiz (40%)|Project (20%)|Project (25%)|Workshop (15%) |
| Timetable | View the lecture timetable | View the full unit timetable |
Textbooks
| Required |
Required readings will be listed in the unit outline prior to the start of classes. |
Links | Booktopia textbook finder |
|---|
The University reserves the right to amend or remove courses and unit availabilities, as appropriate.