NUS
 
ISS
 

Data Science Solutions Implementation

Overview

Reference No TGS-2021009530
Part of -
Duration 4 days
Course Time 6:00pm - 9:00pm / 9:00am - 5:00pm
Enquiry Please contact ask-iss@nus.edu.sg for more details.

Data scientists are generally trained in algorithms and modelling skills. In today’s context, the expectation of the industry of the data scientists have far expanded beyond the scope of just creating models for prediction, optimization, recommendation, etc. Data scientist are expected to be able to deploy such models or work with other teams within the organisation to implement Data Science and Artificial Intelligence (DSAI) models in real production environment.

In addition to technical skills, Data Scientists are also required to report and present to the management and various business stakeholders who often are not familiar with Data Science theory and technical jargons. So as to ensure that the Data Science solutions are appropriately appreciated and adopted, it is of utmost importance that the Data Scientists are equipped with effective communication skills to enable effective key stakeholder engagement and buy-in.

This course is targeted at individuals who develop Data Science and Artificial Intelligence (DSAI) models and are looking to gain some hands-on knowledge of how to deploy such models. The course is also suitable for leaders of DSAI teams who want to be aware of what is required in a DSAI model deployment. As DSAI models can be used in almost all sectors, the audience can be diverse such as, data scientists, and data analysts, who are from any industry such as finance, healthcare and logistics etc.

Over a duration of four (4) days (26 hours) this course will provide attendees with a practical understanding of how to implement and deploy DSAI models in real world environment and also equip them with some effective communication skills.

This course is part of the Data Science Series and an essential component of MTech, Capstone offered by NUS-ISS starting 2022.

 

 

Upcoming Classes

Class 1 24 May 2025 to 14 Jun 2025 (Full Time)

Duration: 4 days

When:
May:
24(Sat), 31(Sat)
Jun:
07(Sat), 14(Sat)
Time:
09:00am to 05:00pm



Key Takeaways

The key areas to be covered are:

  1. DSAI Project Tasks
  2. Implementation Considerations
  3. Cloud Technologies with workshop
  4. Container Technologies and CI/CD pipeline
  5. Deployment considerations
  6. Real Life Deployment Challenges
  7. Effective Communication
 



    Who Should Attend

    • Data Analyst
    • Data Scientist
    • Data Engineer
    • Data Scientist Team Lead

    Prerequisite :

    Participants should have prior experience in any of the following: 

    • Strong coding foundation in programming languages such as R, Python, etc. (mandatory)
    • Familiarity with IDEs such as RStudio, Anaconda, Google Colab etc.
    • Experience in creating data science or artificial intelligence models
    • Comfortable in installing 3rd party software such as Docker, streamlit etc.without supervision.
    • Experience in leading or involved in DSAI projects


    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

     


    Additional Hardware and Software Requirements:
    • Alienware PCs are recommended
    • R & R Studio
    • Python (Anaconda)
    • Docker Desktop
    • Visual Studio Code
    • DBWever (Community edition)



    What Will Be Covered

    • DSAI Project Tasks
    • Implementation Considerations
    • Cloud Technologies with workshop
    • Container Technologies and CI/CD pipeline
    • Deployment considerations
    • Real Life Deployment Challenges
    • Effective Communication
    • Technical Writing



    Fees & Subsidies

    Fees for 2024
      Full Fee Singaporeans & PRs
    (self-sponsored)
    Full course fee S$3600 S$3600
    ISS Subsidy  - (S$360)
    Nett course fee S$3600 S$3240
    9% GST on nett course fee S$324 S$291.60
    Total nett course fee payable, including GST S$3924 S$3531.60
    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%.



    loading

    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

    Register now to learn how to deploy your Data Science and AI solutions effectively.



    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.




    Course Resources

    Develop your Career in the Following
    Training Roadmap(s)

    Please click on the discipline(s) to view the training roadmap of related courses to assess your training needs and goals.

    Data Science

    Driving business decisions using insights from Data

    Read More Data Science

    You Might be Interested in...

    A+
    A-
    Scrolltop
    More than one Google Analytics scripts are registered. Please verify your pages and templates.