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