CS605

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Natural Language Processing for Smart Assistants

Course (UG/PG)

Postgraduate

Offering Unit/Department

Course Description

This course introduces Natural Language Processing (NLP) technologies, which cover the shallow bag-of-word models as well as richer structural representations of how words interact with each other to create meaning. At each level, traditional methods as well as modern techniques will be introduced and discussed, which include the most successful computational models. Along the way, learning-based methods, non-learning-based methods, and hybrid methods for realizing natural language processing will be covered. During the course, the students will select at least 1 course project, in which they will practise how to apply what they learn from this course about NLP technologies to solve real-world problems.

Course Learning Outcomes

. Explain machine learning techniques and algorithms with their use cases in natural language processing.
Apply NLP algorithms and build NLP models in business applications.
Analyze the applicability of NLP algorithms and models.
. Evaluate NLP algorithms and models based on their applicability, effectiveness, efficiencies and business use cases.
. Create and develop NLP models from existing models and algorithms in some new or unique business applications.

Discipline-Specific Competencies

Data Mining and Modelling, Business Intelligence and Data Analytics, Artificial Intelligence Application, Digital Solutioning Skills, Programming and Coding

SMU Graduate Learning Outcomes

Disciplinary knowledge, Interdisciplinary knowledge, Critical thinking & problem solving, Self-directed learning, Resilience

Grading Basis

GRD - Graded