NICF- Reasoning Systems (SF)

NUS Institute of Systems Science

How long?

  • 5 days
  • in person

What are the topics?

NUS Institute of Systems Science


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Who should attend

  • Operation Managers, Business Unit Managers, and Business Professionals who want to learn the use cases and benefits of AI powered intelligent business reasoning systems and core concepts.
  • IT Managers, Enterprise Architects, Application Solution Architects, System Integrators, and Technology Consultants who want to design and integrate hybrid business reasoning solutions
  • IT Analysts who need optimize business resource management using artificial intelligence
  • Data Scientists, Data Engineers, and Data Specialists who want to use AI techniques to reinforce data analytics.
  • IT professionals who want to practice contemporary AI toolsets

About the course

How can you capitalise on the use of Artificial Intelligence – Reasoning Systems to drive innovation and efficiency in your organisation? This 5-day course enables participants to understand the relevant knowledge needed to architect and/or lead teams executing intelligent system projects to reason, simulate, and optimise complex business problems. For example, how to predict future workload and staffing requirements by area, designation, skill and/or role; and how to dynamically redeploy workforce based on unplanned events (sick leave, workload and customer orders fluctuations) in real-time.

Through a mix of lectures reinforced by case examples, participants will acquire comprehensive knowledge of artificial intelligence (AI) techniques, including search, scheduling, optimisation, constraint satisfaction, evolutionary computation, and data mining. Participants will also get hands-on learning to integrate hybrid reasoning systems using computer tools (with some programming) to solve complex and time consuming problems.

Our course participants have been creating intelligent reasoning systems, which use hybrid artificial intelligence techniques learnt: * [Public] video intro for LTA Intelligent Employee Shift Scheduler * [Energy] video intro for Petrol Station Route Optimizer * [Ecommerce] video intro for Delivery Truck Planner, which is an AI enhancement to NICF- Machine Reasoning System: Online Order Management System * [Semiconductor] video intro for Scheduling and Dispatch Optimization, which is an enhancement to NICF- Machine Reasoning System: Lot Disposition Recommendation * [Education] video intro for Intelligent Rapid Shuttle, which is an AI enhancement to NICF- Machine Reasoning System: Smart Secondary School Proposer * [Health] video intro for Patient-Doctor Matcher, which is an AI enhancement to NICF- Machine Reasoning System: Depression Screening System * [Health] video intro for Hospital Nurse Rostering * [Sports] video intro for Yoga Class Scheduling System * [Game AI] video intro for Deck Sorcery: HearthStone Deck Builder * [Industry] video intro for Production Scheduling Optimization System * And more intelligent systems here

This course is for business managers, data specialists, consultants, IT professionals and business professionals interested in learning how reasoning systems with AI optimization techniques can be applied into an organization to drive innovation, efficiency and identify competitive advantages.

This course is a part of the Artificial Intelligence and Graduate Certificate in Intelligent Reasoning Systems, which is a part of the Stackable Graduate Certificate Programme in Artificial Intelligent Systems (Masters Degree) offered by NUS-ISS.

* ### Key Takeaways

Upon completion of the course, participants will be able to:

  • Identify real world business use cases and applications of advanced intelligent reasoning systems.
  • Integrate advanced artificial intelligence enablers in reasoning systems, including heuristic search, constraint satisfaction, simulation assisted learning, evolutionary computation, optimization, planning, system integration, programming, data mining and machine learning algorithms.
  • Decompose complex business/industry scenarios into sub problems to be solved by assembling cooperative intelligent subsystems.
  • Architect hybrid reasoning system by evaluating suitable artificial intelligence techniques and system integration techniques to solve complex problem under business constraints. This is an advanced course with limited in-class coaching of computer programming. Participants with computer programming ability would benefit more during hands-on workshops and project submission as part of course assessment.

  • Participants are required to bring their own internet enabled computing device & power charger to access and download e-courseware in PDF e-copies. This course issues only PDF e-courseware without paper-courseware (Go Green).

  • Participants, who prefer using their own laptop/computer during course workshops,should preinstall iss-vm virtual machine (about 30 GB in size) into own device before course start date.

Participants who attended NICF-Machine Reasoning (SF) course as a prerequisite would transit smoother into this course.

Participants who have not attended NICF-Machine Reasoning (SF) course could self-assess these essential abilities:

  • Able to use computer keyboard and mouse, Windows or Linux or MacOS, Microsoft Office or LibreOffice.
  • Able to read software source code written in one or more programming languages, e.g. web application, class diagram, extensible markup language (XML)
  • Able to write or convert source code into Java, e.g. score calculation Java example:
  • Able to write business rules, e.g. score calculation Drools rule example: cloudBalancingScoreRules.drl
  • Able to operate one or more prevalent integrated development environment (IDE), e.g. Eclipse, IntelliJ, etc.
  • Able to operate one or more prevalent data mining software, e.g. RStudio, Orange, Weka, MATLAB, SPSS, SAS, etc.
  • Able to calculate basic probability.
  • Aware of decision tree, RESTful API, systems development life cycle (SDLC), unified modeling language (UML), client-server software architecture, VMware and/or VirtualBox

What Will Be Covered

This course will cover: Day 1

  • Reasoning Systems Overview
  • Uninformed Search Techniques
  • Search Representation Workshop

Day 2

  • Informed Search Techniques
  • Search Based Intelligent Applications
  • Search Reasoning Workshop

Day 3

  • Reasoning using Optimization Techniques
  • Optimization Based Intelligent Applications
  • Optimization Workshop

Day 4

Knowledge Discovery Using Data Mining / Computer Algorithms Knowledge Discovery Intelligent Applications Knowledge Discovery Workshop

Day 5

  • Hybrid Reasoning Systems
  • Hybrid Reasoning Systems Workshop
  • Course Assessment


Fan Zhen Zhen

Zhenzhen has been with Institute of Systems Science, NUS, since 2006. She currently lectures in the Master of Technology programme in the areas of case-based reasoning, text mining, KBS development, hybrid KBS, and formal specification. Prior to joining ISS, she was a senior research engineer at ...

Zhu Fang Ming

Dr. Zhu Fangming is with the Institute of Systems Science of the National University of Singapore (NUS-ISS). He currently lectures in the Master of Technology programme in the areas of evolutionary computation, neural networks and data mining. Prior to joining ISS, he was a postdoctoral fellow i...

GU Zhan

GU Zhan (Sam) lectures Master of Technology programme in the areas of data science, machine intelligence, soft computing, and applied deep learning. Prior to joining ISS, he was in New Zealand running Kudos Data start-up, which focussed on training programs to democratize artificial intelligence ...

NICF- Reasoning Systems (SF) at NUS Institute of Systems Science

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