Course level

Undergraduate

Faculty

Engineering, Architecture & Information Technology

School

Elec Engineering, Comp Science

Units

2

Duration

One Semester

Attendance mode

In Person

Class hours

Lecture 2 Hours/ Week
Practical 2 Hours/ Week

Prerequisite

MATH1061 and (STAT1201 or STAT1301 or STAT2203 or STAT2003 or STAT2201) and (CSSE1001 or ENGG1001)

Recommended prerequisite

Assessment methods

Quizzes (low stakes)

Individual Assignment

Final Examination

Study Abroad

This course is pre-approved for Study Abroad and Exchange students.

Current course offerings

Course offerings Location Mode Course Profile
Semester 2, 2024 (22/07/2024 - 18/11/2024) St Lucia In Person Profile unavailable

Please Note: Course profiles marked as not available may still be in development.

Course description

The Internet has transformed much of the world¿s knowledge into unstructured text, and the amount of data being made available every day continues to grow exponentially. Developing new techniques to turn this data into knowledge is crucial in the age of information. Processing natural language text is both challenging and rewarding. Learning how to work with web-scale data collections is a critical skill to develop in Computer Science, and understanding the computational methods currently available to achieve scalable data processing will position students to be innovators in AI technologies in their future careers. This course will explore state-of-the-art techniques in natural language understanding and language generation. Students will develop an understanding of the key algorithms used in natural language processing, and be exposed to a diverse range of applications including machine translation, text mining, sentiment analysis, and question answering. Python will be used extensively in this course, and so students are expected to have an intermediate level of knowledge with Python programming.