Course Content
- Introduction to Problem Solving Using Pattern Recognition: Get an overview of the fundamentals and applications of pattern recognition in various fields.
- Solving Classification and Prediction Problems: Explore techniques and algorithms to classify data and make predictions, uncovering underlying patterns.
- Solving Clustering and Anomaly Detection Problems: Learn to group similar data points and detect anomalies, revealing hidden structures and irregularities.
- Component Analysis and Dimension Reduction: Master methods for reducing data dimensions and analysing key components to enhance data interpretation.
- Deep Learning Basics: Gain a foundational understanding of deep learning and its role in pattern recognition.
- Practical Case Studies and Workshops: Apply your knowledge through hands-on case studies and interactive workshops, solidifying your skills in real-world scenarios.
This course is part of the
Artificial Intelligence and
Graduate Certificate in Pattern Recognition Systems Series offered by NUS-ISS.
Key Takeaways
- Translate Real-World Challenges into Pattern Recognition Tasks: Develop the ability to conceptualise real-world problems through the lens of pattern recognition, establishing a strong foundation for devising effective problem-solving approaches.
- Select Appropriate Pattern Recognition Techniques: Identify and apply the most fitting pattern recognition techniques customised to the intricacies of each problem.
- Evaluate and Contrast Pattern Recognition Methods: Analyse and compare various pattern recognition approaches, comprehending trade-offs and guaranteeing optimal solutions across a range of tasks.
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:
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Minimum
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Recommended
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Operating Systems
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• Windows 7 above
• Mac OS
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Laptop running the latest
version of either Windows or
Mac OS
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System Type
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32-bit
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64-bit
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Memory
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8 GB RAM
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16+ GB RAM
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Hard Drive
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256 GB disk size
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Others
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• 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
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Join Us
Enhance your pattern recognition skills.
Register now to unlock the potential of pattern recognition for efficient problem-solving.
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.