Blended Learning Programmes / Programmes / Course BL

Course BL

Overview

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Enquiry	Please email to iss-blendedlearning@nus.edu.sg.

Artificial intelligence (AI) exists in modern computer systems, most times behind the scene. In this course, we reveal those intelligent techniques leading to reasoning ability and smart behaviours embedded in intelligent software systems, which make use of knowledge (digitized data useful to business), learn, reason and take actions automatically, in various business contexts and industry domains.

Participants learn comprehensive knowledge of artificial intelligence (AI) fundamentals, automated computer/machine reasoning methods, knowledge discovery & modelling, decision support technologies, and practice programming to design and architect intelligent machine reasoning systems to solve real-world problems. They will:

● Learn a unique course syllabus from understanding of human intelligence to using machine intelligence and reasoning, and learn to identify needs of machine reasoning technology for decision automation, e.g., developing a project workbook for each individual learner by applying AI Application Framework to decompose and model domain problems using suitable AI techniques.

● Create a software modules with algorithms using modern open-source toolkits, e.g., build a knowledge based industrial soft-bot prototype using bespoke FAQs supplied by individual learners, or using automated knowledge discovery and data mining techniques.

● Gain exclusive access to past projects previews, source code repository and deep know-how delivered by our alumni during theirs Practice Module of NUS-ISS Intelligent Reasoning Systems Graduate Certificate.

Key Takeaways

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

● Identify needs of machine reasoning technology in various industrial applications, for decision automation.

● Acquire knowledge of core machine reasoning techniques, including rule/process-based logical reasoning, domain expert knowledge acquisition and representation, knowledge discovery, and handling uncertainty during reasoning process.

● Apply data mining / machine learning techniques to extract knowledge from data, then express business rules/processes in computer readable format.

● Create software modules with algorithms by applying learnt machine reasoning techniques and computer programming.

● For learners, who successfully completed this course, may advance to other courses from intelligent reasoning systems graduate certificate, practice integration and creation of intelligent software application in practice module.

Structure

● Course duration: 8 weeks (online).

● Learners are recommended to set aside three to four hours of focused learning time to get the most out of the course.

● This course is designed to be self-paced and cohort-based, with 3 synchronous live sessions via Zoom. Content will be released on a weekly basis.

● Throughout the course, learners are expected to actively contribute to the group activities and are encouraged to apply the knowledge learnt. They will have ample opportunities to do so via discussions, peer learning, workshops, assessments, and applications.

Who Should Attend

This course is appropriate for IT professionals with programming experiences moving into design and development of intelligent software modules/functions/APIs for business insights extraction, knowledge retention, decision automation and optimization using AI techniques, and will be useful for:

● Artificial Intelligence Engineer who need develop competency in knowledge modelling, representation, discovery, knowledge graph, knowledge/rule base, and machine inference.

● Software Developer/Engineer who need develop competency in business rule management system (BRMS) and business process management system (BPMS).

● Application Solution Architect who need design intelligent system solutions and integrate them into enterprise system architecture.

● Data Scientist/Engineer who need obtain domain knowledge in artificial intelligence to assist data analytics.

● Working professionals who need to upgrade existing machine reasoning knowledge and skills by practicing contemporary system building tool sets.

Instructors

Dr. Gary LEUNG

Senior Lecturer & Consultant, Artificial Intelligence Practice

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Fees And Funding

Type of Learners	Course Fee	Total course fee payable, including GST
Learners residing in Singapore (SGD)	SGD 1,100	SGD 1,199
Learners residing outside Singapore (USD)	USD 850	USD 850

Things To Note

● Learners are expected to set aside time for group activities beyond the live sessions.

● The NUS-ISS Certificate of Completion will be issued to learners who have met the course requirements successfully. This will include attending all synchronous Zoom sessions and completing the learning activities, workshops and assessments (where applicable).

● Read the terms and conditions of NUS-ISS Course Registration here.

● Read about NUS-ISS and Learner’s Commitment and Responsibilities here.

● All classes are subject to confirmation and NUS-ISS will send an acceptance email to learners one week prior to the commencement date.

● All responses to feedback and surveys conducted by NUS-ISS and its partners must be submitted by learners.

● All trainings and assessments will be delivered by NUS-ISS, as described in the course webpage.

● For general enquiries and feedback, please feel free to reach out to us via email at iss-blendedlearning@nus.edu.sg.

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