Key Takeaways
At the end of the course, the participants will be able to:
Identify where sentiment analysis can be applied
Evaluate and analyse the classification techniques for sentiment classification and apply it with open source libraries
Design a sentiment analysis system for customer feedback and reviews
Design a sentiment analysis system for news and social media for applications in finance
Evaluate and assess sentiment analysis at a granular level for entities and aspects
Who Should Attend
This is an intermediate course, suitable for professionals with an interest or requirement to understand digital marketing and social engagement for customers.
It is applicable for professionals engaged in the following areas.
Customer analysts performing deeper analytics on sentiment analysis on customer feedbacks and reviews
Data scientists in financial services doing applied sentiment mining for applications in finance including fraud, trading.
Data analysts in the financial services who use internal research and external news for research.
Analysts who want to automate and extract insights from the voluminous internal and external textual documents in their organisations
Prerequisites
- Participants must successfully completed Text Analytics course offered by NUS-ISS.
- Participants must have strong programming skills using python, familiar with packages like Numpy, Pandas, Scikit-Learn, and well versed using virtual environments in python (GitHub or CoLab).
- Interested participants who did not take the Text Analytics course offered by NUS-ISS must take a precourse assessment quiz and pass it. The precourse assessment quiz is administered online and tests the participant’s practical understanding of text mining concepts necessary to undertake this course successfully. The assessment does not test programming skills.
What to Bring
No printed copies of course materials are issued.
Participants must bring their internet-enabled computing device (laptops, tablet etc) with power charger to access and download course materials.
If you are bringing a laptop, please see below for the tech specs:
|
Minimum
|
Recommended
|
Operating Systems
|
• Windows 7, 8, 10 or
• 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
|
What Will Be Covered
Introduction to sentiment analysis and its applications in various social domains.
Overview of related tasks of NLP to sentiment analysis
Supervised learning classification algorithms for sentiment analysis
Entity and aspect mining for sentiment analysis
Sentiment visualization tools
Applications of sentiment analysis to customer analytics and financial applications
Sentiment analysis and its psychological basis
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:
- All fees and subsidies are valid from January 2024, unless otherwise advised.
- 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.
- From 1st January 2024, the GST will be increased to 9%.
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.
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.