Program details
Introduction
NLP focuses on system development that allows computers to communicate with people using everyday language. Natural language generation systems convert information from the computer database into readable or audible human language and vice versa. Such systems also enable sophisticated tasks such as inter-language translation, semantic understanding, text summarization and holding a dialog. The key applications of NLP algorithms include interactive voice response applications, automated translators, digital personal assistants (e.g., Siri, Cortana, Alexa), chatbots, and smart word processors.
Program
Competence
Upon completion of the program requirements, the graduate will be able to:
- Demonstrate highly specialized understanding of the computational techniques for analyzing and modelling textual and speech data with applications to real-world scenarios.
- Have a deep understanding of the syntactic and semantic structures in speech and textual data (e.g. the predicate-argument structure).
- Obtain advanced capabilities to implement cutting-edge NLP algorithms, and benchmark the achieved results.
- Have the capability to formulate their own research questions, analyze the existing body of knowledge, propose and develop solutions to new problems.
- Obtain expertise in using and deploying NLP related programming tools for a variety of NLP problems.
- Work independently as well as part of a team, in a collegial manner, on NLP-related projects.
- Manifest the right learning attitude during coursework and research that clearly shows ownership, personal and technical growth and responsibility.
- Effectively communicate experimental results and research findings orally and in writing, and critique existing body of work.
The minimum degree requirements for the Master of Science in Natural Language Processing are 35 Credits, distributed as follows:
Core Courses
MSc in Natural Language Processing is primarily a research-based degree. The purpose of coursework is to equip students with the right skillset, so they can successfully accomplish their research project (thesis). Students are required to take COM701, as a mandatory course. They can select three core courses from a concentration pool of six in the list provided below:
COM701 Research Communication and Dissemination*
NLP701 Natural Language Processing
NLP702 Advanced Natural Language Processing
NLP703 Speech Processing
MTH701 Mathematical Foundations for Artificial Intelligence
AI701 Artificial Intelligence
AI702 Deep Learning
Elective Courses
Students will select a minimum of two elective courses, with a total of eight (or more) credit hours (CH) from a list of available elective courses based on interest, proposed research thesis, and career perspectives, in consultation with their supervisory panel. The elective courses available for the Master’s of Natural Language Processing are listed in below table:
MTH702 Optimization
CS701 Advanced Programming
CS702 Data Structures and Algorithms
DS701 Data Mining
DS702 Big Data Processing
ML701 Machine Learning
ML702 Advanced Machine Learning
ML703 Probabilistic and Statistical Inference
NLP701 Natural Language Processing
NLP702 Advanced Natural Language Processing
NLP703 Speech Processing
CV704 Advanced Computer Vision
CV705 Advanced 3D Computer Vision
CV706 Neural Networks for Object Recognition and Detection
HC701 Medical Imaging: Physics and Analysis
Research Thesis
The Master’s thesis exposes students to an unsolved research problem, where they are required to propose new solutions and contribute towards the body of knowledge. Students pursue an independent research study, under the guidance of a supervisory panel, for a period of 1 year.
NLP699 Master’s Research Thesis