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Short Course

Chatbot Development Begins With Me

Programme ScheduleDuration (days)Mode of DeliveryProgramme Code
To be advised1Classroom LearningTGS-2025056386
To be advised1Synchronous e-LearningTGS-2025056387
This course is offered once a year.

Course Overview

Chatbots on the mobile phone or website are becoming a popular method to interact with and service an organisation’s customers. This one-day programme will enable participants to build a basic Chatbot with no programming requirements. It is designed for organisations wanting to build and launch a Chatbot service on their web or as a mobile service.

Course Objectives

At the end of the course, participants will be able to:

  • Understand the tools and landscape of the Bot ecosystem
  • Build a basic FAQ bot for an organisation
  • Deploy the bot into a website or integrate with a bot channel such as Skype, Webchat or Slack
  • Handle technical queries with the capabilities to build a useful and relevant Chatbot system.
  • Use an online and comprehensive Chatbot system to quickly develop and deploy a real conversation style FAQ Chatbot system at minimal costs.

Who Should Attend

Software Engineers, Programmers, Business Analysts, Data Analysts, Frontline Staff, Customer Service Officers

Prerequisites

Preferably with experience in Python and Google Cloud AI

Technical Requirements

Dialogflow

Note: It is COMPULSORY for participants to have a Google Account and Telegram Account set up, and with Google Assistant installed in their mobile phones in order to attend this course.

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This programme is part of

  • Professional Certificate in Digital Marketing & Customer Insights

    • Types of Available Fundings

  • SkillsFuture Funding
  • SkillsFuture Credit
  • Enhanced Training Support
  • SFEC
  • UTAP
  • PSEA

    • Testimonials


    Well structured and good for beginners. Highly recommended.

    Jennie Lim Poh Kee

    Good course for ChatBot.

    Kee Boon King

    This course really guides you to build a simple chatbot.

    Anonymous

    Instructors


    Dr Edmund Low

    Dr Edmund Low

    Dr Edmund Low is currently Senior Lecturer with the NUS College at the National University of Singapore. He has nearly 20 years of academic and professional experience in the use of data-driven tools to answer questions in public health and the environment. His past projects include applying AI techniques and machine learning models for environmental modelling and impact assessment. He currently heads the quantitative reasoning domain at USP, and teaches courses on statistical methods, data science and machine learning. As an educator, Edmund is a multiple recipient of both the USP Teaching Excellence Award, as well as the NUS Annual Teaching Excellence Award. Edmund holds a PhD in Environmental Engineering from Yale University.

    Ms Samantha Sow

    Ms Samantha Sow

    Ms. Samantha Sow is currently a Senior Lecturer in the department of Information Systems and Analytics at the National University of Singapore (NUS). She has over 8+ years of experience in Business Analytics and Data Science and she conducts training for both government agencies and corporate clients. Before joining NUS, she lectures at Temasek Polytechnic, teaching Business Analytics and Data Science to professionals, managers and executives (PMEs). Prior to being an academia, Samantha worked in the research and development at Infineon Technologies. Her research and project areas include Business Analytics, Data Mining, Predictive and Prescriptive Analytics. She has a passion for engaging and inspiring participants to enhance their workplace analytics capabilities and increase business intelligence quotient within their organisations. Her interests lie in the applications of data analytics, predictive modelling and optimization techniques to derive actionable insights for commercial effectiveness. She is familiar with typical analytics tools such as Python, R, and SAS, SPSS and Tableau. She also has working knowledge in the area of Analytics, Data Science and Machine Learning. Samantha completed her Master of Education from University of Sheffield and graduated from the National University of Singapore with a Bachelor’s in Engineering, First Class Honours. She has also completed THEC (Teaching in Higher Education) and ACTA (Advanced Certificate in Training and Assessment). She is a member of the adult associate educator (AEN) by Institute for Adult Learning (IAL), Singapore. Her certifications include: Microsoft Certified Azure Data Scientist Associate. Microsoft Certified Data Analyst Associate. SAS Certified Predictive Modeller in SAS Enterprise Miner. Tableau Certified Desktop Specialist.

    Programme Fees


    Singapore Citizens Singapore PRs Enhanced Training Support for SMEs International Participants
    39 years old
    or younger    		 40 years old
    or older
    Full Programme Fee S$850.00 S$850.00 S$850.00 S$850.00 S$850.00
    9% GST on Full Programme Fee S$76.50 S$76.50 S$76.50 S$76.50 S$76.50
    Less: SSG Grant Amount S$425.00 S$425.00 S$425.00 S$425.00 -
    Nett Programme Fee S$425.00 S$425.00 S$425.00 S$425.00 S$850.00
    Total Nett Programme Fee Payable, Including GST S$501.50 S$501.50 S$501.50 S$501.50 S$926.50
    Less Additional Funding - S$170.00 - S$170.00 -
    Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes S$501.50 S$331.50 S$501.50 S$331.50 S$926.50
    1. Total Nett Programme Fee Payable, including GST, after additional funding from various funding schemes.
    2. Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.
    3. The applicable funding is for Singaporeans and Singapore PRs. This is subject to change and in accordance with SSG funding guidelines as of course commencement.

    Other Information

    This course is eligible for Union Training Assistance Programme (UTAP). NTUC members can enjoy up to 50% funding (capped at $250 per year) under UTAP. NTUC members aged 40 and above can enjoy higher funding support up to $500 per individual each year, capped at 50% of unfunded course fees, for courses attended between 1 July 2020 to 31 December 2025. Please click here for more information.

    NUS Computing, Advanced Computing for Executives (ACE)

    11 Research Link
    COM 3, #B1-07
    Singapore 119391

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