NUS
 
ISS
 

Explainable and Responsible Artificial Intelligence

Overview

Reference No TGS-2023018994
Part of -
Duration 3 days
Course Time 9:00am - 5:00pm
Enquiry Please email ask-iss@nus.edu.sg for more details.

The field of Artificial Intelligence (AI) has been gaining increasing attention in the recent years. There has been widespread adoption of AI for use in almost all industries and for various purposes.

With the pervasive and widespread use of AI, there have been cases of AI hiccups or cases of AI bias reported in various applications. It has become inevitable that the spotlight is slowly shifting from how AI models can be applied to the need for Explainable & Responsible AI (XRAI).

The emphasis on XRAI is important in order to promote AI innovation and adoption, as well as to gain trust and confidence in the users of AI. Therefore, there is a need for further research, development and discussion in the AI community concerning the various aspects of XRAI. In the recent years, there is a rise in the creation of software tools and guidelines related to this area by the technology companies and regulators of various countries.

This course is intended for participants who are users of AI models or developers of AI models, for example, human resource recruiters using AI hiring algorithms, developers of AI facial recognition systems, marketing analysts using advertisement recommendation AI engines, etc.

This course is part of the Artificial Intelligence and Data Science series offered by NUS-ISS.

Upcoming Classes

Class 1 01 Jul 2024 to 03 Jul 2024 (Full Time)

Duration: 3 days

Time:
09:00am to 05:00pm



Key Takeaways

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

  • Understand what is Explainable and Responsible AI and recognize AI adoption consideration factors
  • Identify data factors that affect AI algorithm performance
  • Assess the mitigating measures to prevent potential data issues
  • Know how to achieve better AI project transparency
  • Know how to assess the required level of human intervention
  • Appraise and explain the requirements of AI model update and review
  • Know the working mechanism of a black box model and what are the tools for Explainable AI
  • Assess the fairness of the AI model and explore bias reduction strategy
  • Understand and analyze model vulnerabilities and know the mitigating factors for adversarial attacks
  • Apply ethical considerations for designing or using AI solutions
  • Know how to implement Responsible AI framework in different scenarios



Who Should Attend

This course is intended for participants who are users of AI models or developers of AI models.

The target audience would be, for example,

  • AI Analyst
  • AI Engineer
  • AI Scientist
  • AI Architect
  • AI Product Manager
  • AI Project Manager
  • AI users (of various departments in organisation, for example, HR, Marketing, etc.)

Pre-requisites

  • Good understanding of AI models and its usage
  • Have experience working with AI models or as user of AI models


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 Software Requirements:

• Python (Anaconda)
• Google Colab
• R & R Studio
• Excel - Analysis Toolpak



What Will Be Covered

This course will cover:

  • Introduction to Explainable and Responsible AI
  • Stages of AI model development and how XRAI is relevant to these stages
  • Explainable AI
  • Bias and Fairness of AI Model
  • Vulnerability of AI Model
  • Ethical Considerations in AI
  • Responsible AI Framework



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

The ISS Certificate of Completion will be issued to participants who have attended at least 75% of the course and pass the required assessments.




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

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