NUS
 
ISS
 

New Media and Sentiment Mining

Overview

Reference No TGS-2020001445
Part of Graduate Certificate in Practical Language Processing
Duration 3 days
Course Time 9.00am - 5.00pm
Enquiry Please contact ask-iss@nus.edu.sg for more details.

Are you harnessing the influx of textual data from customers, internal documents, emails, news articles, and social media? These texts are rich with opinions and sentiments that can be automatically extracted using the latest DNN techniques and Generative AI tools.

To stay ahead in the new media landscape, businesses must process and analyse vast amounts of textual data across various social media platforms to decipher the sentiments embedded within, in order to identify emerging issues, monitor brand reputation, and make informed decisions. This course equips you to design sentiment analysis systems for diverse applications and introduces sentiment analysis and its practical uses, giving you the skills to evaluate supervised learning algorithms for sentiment classification and to interpret detailed meanings in texts.

new media 1

new media 2

Upcoming Classes

Class 1 26 Jul 2025 to 16 Aug 2025 (Full Time)

Duration: 3 days

When:
Jul:
26(Sat)
Aug:
02(Sat), 09(Sat)
Time:
09:00am to 05:00pm

Class 2 27 Oct 2025 to 29 Oct 2025 (Full Time)

Duration: 3 days

When:
Oct:
27, 28, 29
Time:
09:00am to 05:00pm



Course Content

  • Introduction to Sentiment Analysis: Discover the fundamentals of sentiment analysis and its applications across various social domains.
  • Deep Neural Networks for Feature Learning: Harness the power of embeddings like word2vec, GloVe, and GenAI to learn features using deep neural networks.
  • Entity and Aspect Extraction: Extract entities and aspects from text, focusing on products, brands, features, and attributes.
  • Advanced Sentiment Mining Techniques: Apply different approaches for sentiment mining, including supervised learning, deep learning, and zero-shot learning with Large Language Models (LLMs).
  • Model Evaluation and Comparison: Evaluate and compare the performance of various sentiment mining models and methods.
  • Sentiment Visualisation Tools: Learn to visualise sentiment analysis results effectively.
  • Hands-on Experience: Gain practical experience with popular frameworks and libraries such as TensorFlow, PyTorch, HuggingFace Transformers, and spaCy. Work with real-world datasets and case studies from IMDb, Amazon, Yelp, and Twitter.
This course is part of the Artificial Intelligence and Graduate Certificate in Practical Language Processing Series offered by NUS-ISS.

Key Takeaways

  • Identify Sentiment Analysis Opportunities: Understand where sentiment analysis can be effectively applied across different domains.
  • Practical Application: Apply sentiment mining techniques in marketing, customer service, product development, and social media analysis.
  • Model Development and Deployment: Build and deploy your own sentiment mining models and systems using state-of-the-art technologies and Generative AI tools.
  • Granular Sentiment Evaluation: Evaluate and assess sentiment analysis at a detailed level for specific entities and aspects.
  • Advanced Skills Enhancement: Enhance your expertise in the rapidly evolving field of sentiment mining using deep learning and Large Language Models (LLMs).



    Who Should Attend

    • Data Analysts, Business Users, and IT Professionals: Elevate your understanding of digital marketing and social engagement through advanced sentiment analysis techniques.
    • Customer Analysts: Perform deeper analytics on customer feedback and reviews to uncover nuanced sentiments and improve customer experience.
    • Financial Services Analysts: Utilise sentiment analysis on internal research and external news to enhance financial research and decision-making.
    • Data Scientists: Automate the extraction of insights from large volumes of internal and external textual data using Generative AI tools.



    Prerequisites




    Course Logistics

    • No Printed Materials: Course materials are accessed digitally. Do kindly note that no printed copies of course materials will be issued.
    • Device Requirements: Bring an internet-enabled device (laptop, tablet, etc) with power chargers to access and download course materials.
    If you are bringing a laptop, kindly refer to the table below for the recommended tech specs:

     

     

    Minimum

    Recommended

    Operating Systems

    • Windows 7 above
    • Mac OS

    Laptop running the latest
    version of either Windows or
    Mac OS

    System Type

    32-bit

    64-bit

    Memory

    8 GB RAM

    16+ GB RAM

    Hard Drive

    256 GB disk size

     

    Others

    • An internet connection – broadband wired or wireless
    • Installation permissions (non-company laptops)
    • Keyboard
    • Mouse/Trackpad
    • Display
    • Power adapter (laptop battery might run out)

    DirectX 10 graphics card for graphics hardware acceleration

     
     



    Fees & Subsidies

    Fees for 2024
      Full Fee Singaporeans & PRs
    (self-sponsored)
    Full course fee S$2700 S$2700
    ISS Subsidy  - (S$270)
    Nett course fee S$2700 S$2430
    9% GST on nett course fee S$243 S$218.70
    Total nett course fee payable, including GST S$2943 S$2648.70
    Note:
    1. All fees and subsidies are valid from January 2024, unless otherwise advised.
    2. All self-sponsored Singaporeans aged 25 and above can use their SkillsFuture Credit to pay for course fees. For more information about SkillsFuture Credit, click here.
    3. From 1st January 2024, the GST will be increased to 9%.



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    Certificate

    Certificate of Completion
    Participants have to meet a minimum attendance rate of 75% and are required to pass the assessment to be issued a Certificate of Completion.



    Join Us

    Elevate your data analysis capabilities. Register now to discover sentiment insights from text data.




    Preparing for Your Course

    NUS-ISS Course Registration Terms and Conditions

    Find out more.

    NUS-ISS and Learner’s Commitment and Responsibilities

    Find out more.

    WIFI Access

    WIFI access will be made available to participants.

    Venue

    NUS-ISS
    25 Heng Mui Keng Terrace
    Singapore 119615

    Click HERE for directions to NUS-ISS

    In the event of a change of venue, participants are advised to refer to the acceptance email sent one week prior to the commencement date.

    Course Confirmation

    All classes are subject to confirmation and NUS-ISS will send an acceptance email to participants one week prior to the commencement date. Confirmed registrants are to attend and complete all lectures, class exercises, workshops and assessments (where applicable). Additionally, all responses to feedbacks and surveys conducted by NUS-ISS and its partners must be submitted. All training and assessments will be delivered as described in the course webpage.

    General Enquiry

    Please feel free to write to ask-iss@nus.edu.sg if you have any enquiry or feedback.




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