NUS
 
ISS
 
NUS ISS

Spatial Reasoning from Sensor Data


Navigate the World: Master the Art of Spatial Intelligence from Sensor Data

Overview

Reference No TGS-2020001513
Part of Graduate Certificate in Intelligent Sensing Systems
Duration 3 days
Course Time 9.00am - 5.00pm
Enquiry Please email ask-iss@nus.edu.sg for more details

How can you transform raw sensor data into smart decisions for spatial reasoning?

Unlock the potential of spatial sensing and reasoning technology in this course, designed for professionals seeking to master the art of interpreting sensor data for a variety of cutting-edge applications. Once reserved for specialised enterprise and industrial use, such as urban planning and robotic navigation, these technologies have now expanded into a plethora of markets, including automotive, consumer goods, and industrial sectors.

This course not only lays the theoretical groundwork but also emphasises practical skills through practical workshop sessions. Participants will engage in practical activities to simulate real-world scenarios, applying spatial sensing and reasoning techniques to solve complex problems.

Upcoming Classes

Class 1 22 Feb 2025 to 08 Mar 2025 (Full Time)

Duration: 3 days

Time:
09:00am to 05:00pm


Course Content

  • Spatial Sensing: 3D sensor data representation and modelling.
  • Spatial Reasoning: Place localisation and recognition from sensory data (e.g., NetVLAD).
  • Spatial Recognition: Object and scene recognition from 3D data using deep learning (e.g., PointNet).
  • Practicality: Practical case studies and workshops.
This course is part of the Artificial Intelligence and Graduate Certificate in Intelligent Sensing Systems Series offered by NUS-ISS.

Key Takeaways

  • Master the essential principles of spatial sensing and reasoning technologies, encompassing scene representation, scanning, mapping, and the utilisation of both feature-based and advanced machine learning methodologies.
  • Develop the ability to critically analyse, evaluate, and synthesise solutions for complex spatial sensing and reasoning challenges.
  • Gain practical experience in constructing spatial sensing and reasoning systems, with applications extending to robotics, augmented reality, and other innovative fields.


    Who Should Attend

    • Data Scientists seeking to enhance their analytical skills in interpreting 3D sensor data for spatial reasoning tasks.
    • Product Managers responsible for initiating and overseeing projects and products that incorporate spatial reasoning technologies.
    • Solution Architects aiming to embed spatial reasoning functionalities into intelligent sensing solutions as part of their system design.
    • Robotic System Managers who leverage 3D vision technology to augment the spatial reasoning capabilities of robotic systems.


    Prerequisites

  • Participants should have intermediate skills in Python programming (e.g. Numpy, Pandas), and/or OpenCV programming (e.g. able to apply filtering and transformation on the image).
  • Experienced in using Jupyter Notebooks, Google Colab and well-versed in package installation.
  • Participants must have an intermediate knowledge of computer vision at the level of Vision Systems (e.g. image processing, image classification and object detection using deep learning).


    • 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

    • Windows 7 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 & 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

    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 start your journey of mastering spatial reasoning capabilities.



    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.



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