Course Content
- Introduction to Reasoning Systems: Understand the evolution from human to machine intelligence and the fundamentals of AI applications in reasoning.
- Architectures of Reasoning Systems: Explore the structures and cognitive functions of reasoning systems, including learning, perceiving, and acting.
- Knowledge Representation Techniques: Learn essential techniques for representing and acquiring knowledge, building, and utilising knowledge bases.
- Deductive Reasoning and Logical Inference: Develop proficiency in deductive reasoning and logical inference, constructing and applying logical models.
- Reasoning Under Uncertainty: Study methods for handling uncertainty, including probabilistic reasoning and decision-making under various conditions.
- Contemporary Reasoning Systems: Master the use of modern reasoning systems that integrate big data and machine learning for knowledge discovery and problem-solving.
You will gain practical experience through scenario-based case studies and hands-on sessions using popular tools and frameworks.
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 offered by NUS-ISS.
Key Takeaways
- Comprehensive Understanding of Machine Reasoning: Grasp the evolution of machine reasoning, its applications, and the architecture of reasoning systems.
- Knowledge Representation: Learn techniques for representing and acquiring knowledge, essential for enabling machine reasoning.
- Deductive and Inductive Reasoning: Develop skills in deductive reasoning and logical inference, constructing and applying logical models to solve complex problems.
- Handling Uncertainty: Understand methods for reasoning under uncertainty, including probabilistic reasoning and decision-making under various conditions.
- Integration with Big Data and Machine Learning: Discover how contemporary reasoning systems leverage big data and machine learning for knowledge discovery and problem-solving.
Who Should Attend
- IT Professionals, Data Scientists, AI Enthusiasts: Enhance your AI skills by incorporating advanced machine reasoning into your toolkit.
- Professionals Handling Complex Decision-Making: Business and IT professionals seeking to elevate their analytical skills to design and implement reasoning systems that handle complex decision-making processes for optimising operations and strategic planning.
- Anyone Interested in Intelligent Systems: Anyone interested in developing intelligent systems capable of reasoning, learning, and acting autonomously to solve complex problems and innovate solutions in various domains.
Prerequisites
- Competent in Python programming.
- Experienced in using Jupyter Notebooks, Google Colab, and well-versed in package installation.
Course Logistics
- No Printed Materials: Course materials are accessed digitally. Do kindly note that no printed copies of course materials will be issued.
- Device Requirements: Bring an internet-enabled device (laptop, tablet, etc) with power chargers to access and download course materials.
If you are bringing a laptop, kindly refer to the table below for the recommended tech specs:
|
|
Minimum
|
Recommended
|
|
Operating Systems
|
• Windows7 and above
• 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
|
Fees and Subsidies
SkillsFuture Singapore (SSG) Funding 2024
| |
Full Course Fees |
Singapore Citizens & PRs aged 21 years and above
(70% funding support) |
Singapore Citizens aged 40 years and above
(90% funding support) |
Enhanced Training Support for SMEs (ETSS)
(90% funding support)
|
| Full course fee |
S$3800 |
S$3800 |
S$3800 |
S$3800 |
| SSG Funding |
- |
S$2660 |
S$2660 |
S$2660 |
| Nett course fee |
S$3800 |
S$1140 |
S$1140 |
S$1140 |
| 9% GST on nett course fee |
S$342 |
S$102.60 |
S$102.60 |
S$102.60 |
| Additional Funding if eligible under various schemes |
- |
- |
S$760 |
S$760 |
| Total nett course fee payable, including GST |
S$4142 |
S$1242.60 |
S$482.60 |
S$482.60 |
Note:
1. SSG Funding is available to qualified individuals, subject to meeting the attendance requirement and passing of assessment.
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. SME fees are applicable only to participants who are sponsored by small and medium enterprises.
4. SSG Funding is valid up to 30 Sep 2024.
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 harness the full potential of intelligent decision-making systems and drive innovation in your organisation.
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.