Advanced Certificate in Artificial Intelligence in the Digital Economy Module 3: Natural Language Processing and Sentiment Analysis
- Analytics & Tech
- Innovation & Business Improvement
This module is conducted in-person.
2 days (Weekdays)
Who Should Attend
- Professionals in data science, artificial intelligence, digital marketing, customer experience management, and business analytics, alongside those interested in language processing and sentiment analysis applications across industries.
PREREQUISITES
There are no prerequisites for this programme. Prior knowledge on any of the topics is not required
Overview
This module provides a comprehensive understanding of how artificial intelligence (AI) techniques can be applied to analyse and understand human language. It covers the fundamental concepts of natural language processing (NLP) including tokenization, stemming, lemmatization, part-of-speech tagging, and syntactic parsing. Participants will also delve into sentiment analysis which involves using NLP techniques to determine the sentiment or emotional tone behind a piece of text. They will learn about various approaches to sentiment analysis such as lexicon-based methods, machine learning based methods, and deep learning models for sentiment classification. Furthermore, this module equips participants with practical skills in implementing NLP and sentiment analysis algorithms using popular libraries such as NLTK (Natural Language Toolkit), spaCy, and TensorFlow.
Through hands-on projects and case studies, participants will gain valuable experience in applying these techniques to real-world problems in areas such as social media monitoring, customer feedback analysis, market research, and more. By the end of this module, participants will have developed a strong foundation in NLP and sentiment analysis within the context of AI applications in the digital economy. They will be able to leverage these skills to extract meaningful insights from textual data that can drive informed decision-making across various industries.
Learning Objectives
At the end of the 2-day module, participants will be able to:
- Understand the fundamental concepts and techniques of natural language processing (NLP) and how they are applied in various real-world applications
- Develop proficiency in using NLP tools and libraries to process, analyse, and extract meaningful information from unstructured text data
- Gain practical experience in sentiment analysis by learning how to classify and interpret emotions, opinions, and attitudes expressed in textual content
- Explore advanced NLP models such as recurrent neural networks (RNNs) and transformers for more complex language understanding tasks
- Apply NLP techniques to solve business challenges related to customer feedback analysis, social media monitoring, and other relevant use cases within the digital economy landscape
Assessment
As part of the requirement for SkillsFuture Singapore, there will be an assessment conducted at the end of the course. The mode of assessment, which is up to the trainer’s discretion, may be an online quiz, a presentation or based on classroom exercises.
Participants are required to attain a minimum of 75% attendance and pass the associated assessment in order to receive a digital Certificate of Completion issued by Singapore Management University.
Calculate Programme Fee
Fee Table
| EMPLOYER-SPONSORED | |||
|
PARTICIPANT PROFILE |
SELF-SPONSORED |
SME |
NON-SME |
|
Singapore Citizen < 40 years old Permanent Resident LTVP+
|
$654 (After SSG Funding 70%) |
$254 (After SSG Funding 70% |
$654 (After SSG Funding 70%) |
|
Singapore Citizen ≥ 40 years old |
$254 (After SSG Funding 70% |
$254 (After SSG Funding 70% |
$254 (After SSG Funding 70% |
|
International Participant |
$2,180 (No Funding) |
$2,180 (No Funding) |
$2,180 (No Funding) |
All prices include 9% GST
Please note that the programme fees are subject to change without prior notice.
Post Secondary Education Account (PSEA)
PSEA can be utilised for subsidised programmes eligible for SkillsFuture Credit support. Click here to find out more.
Self Sponsored
SkillsFuture Credit
Singapore Citizens aged 25 and above may use their SkillsFuture Credits to pay for the course fees. The credits may be used on top of existing course fee funding.
This is only applicable to self-sponsored participants. Application to utilise SkillsFuture Credits can be submitted when making payment for the course via the SMU Academy TMS Portal, and can only be made within 60 days of course start date.
Please click here for more information on the SkillsFuture Credit. For help in submitting an SFC claim, you may wish to refer to our step-by-step guide on claiming SkillsFuture Credits (Individual).Workfare Skills Support Scheme
From 1 July 2023, the Workfare Skills Support (WSS) scheme has been enhanced. Please click here for more details.
Employer Sponsored
Enhanced Training Support for SMEs (ETSS)
- Organisation must be registered or incorporated in Singapore
- Employment size of not more than 200 or with annual sales turnover of not more than $100 million
- Trainees must be hired in accordance with the Employment Act and fully sponsored by their employers for the course
- Trainees must be Singapore Citizens or Singapore Permanent Residents
- Trainees must not be a full-time national serviceman
- Trainees are eligible for ETSS funding only if their company's SME status is approved prior to the course commencement date. To verify your SME's status, please click here.
Please click here for more information on ETSS.
Absentee Payroll
Employers who sponsor their employees for the course may apply for Absentee Payroll here. For more information, please refer to:
AP Guide (Non-SME Companies)
Declaration Guide (SME Companies)
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*Online registration will close 5 calendar days before the course start date
