NICF – Pattern Recognition with Pytorch | WSQ Courses

Originally published at: NICF – Pattern Recognition with Pytorch | WSQ Courses – WSQ courses | SkillsFuture Courses

Digital Signal Processing is a domain on how to process any kind of signal whether it is waveform, audio, image, so.that we ca transform the signal and extract useful information from the signals. It can be applied to speech recognition, image processing, signal identification problems.

On the other hand, Machine Learning is a domain on how to build a model for the data in order to perform some tasks like regression, classification, clustering, feature reduction. It is therefore useful to apply machine learning techniques to signal processing.

This WSQ course will teach you various machine learning algorithms such as neural network, convolutional neural network, recurrent networking using the powerful Pytorch framework developed by Facebook. In addition, it will teach you how to apply machine learning techniques to signal processing tasks.

Course Objectives

Learners will be able develop machine learning systems using Pytorch

Course Learning Outcomes

By the end of the course, learners will be able to

  • assess various machine learning techniques across different application domains
  • apply machine learning techniques to regression and classification problems.
  • solve temporal sequential problem using recurrent neural network
  • build pattern recognition systems using convolutional neural network
  • apply machine learning techniques to signal processing

Course Brochure

Download NICF – Pattern Recognition with Pytorch Brochure

Skills Framework

This course follows the guideline of Pattern Recognition Systems ICT-DIT-5026-1.1 TSC under ICT Skills Framework

Certification

Two e-certificates will be awarded to trainees who have demonstrated competency in the WSQ assessment and achieved at least 75% attendance.

  • A SkillsFuture WSQ Statement of Attainment (SOA) issued by WSG. Typically will take 3-4 weeks.
  • Certification of Completion issued by Tertiary Infotech Pte Ltd issued after the class.

WSQ Funding

WSQ funding is only applicable to Singaporeans and PR. Subject to eligibility, the funding support is subjected to funding caps.

Effective for courses starting from 1 Jan 2023
Full Fee GST Nett Fee after Funding (Incl. GST)
Normal MCES / SME
$688 $55.04 $399.04 $261.44

Normal: Singaporean/PR age 21 and above
MCES: Singaporean age 40 and above

WSQ TG Application Form

Eligible individuals and company can apply for WSQ TG. Please login to Skilleto and fill in the required details for grant application. Please click here to submit for WSQ TG

Please do not pay upfront. We will advise you on the eligibility and nett fee after registration. Company sponsored staff are eligible for Absentee Payroll.


After the WSQ subsidy, you can offset the nett fee by the following :

SkillsFuture Enterprise Credit (SFEC)

Eligible Singapore-registered companies can tap on $10000 SFEC to cover up out-of-pocket expenses.Click here to submit SkillsFuture Enterprise Credit

SkillsFuture Credit

Eligible Singapore Citizens can use their SkillsFuture Credit to offset course fee payable after funding. Click here for SkillsFuture Credit submission

PSEA

Eligible Singapore Citizens can use their PSEA funds to offset course fee payable after funding. Click here for ad-hoc PSEA application form.

UTAP

Eligible NTUC members can apply for 50% cash rebate of the unfunded fee from UTAP, capped at $250 per year. Click here to submit UTAP

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Courses are provided by tertiarycourses.com.sg