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WSQ - Building Advanced Machine Learning and AI Solutions with Pytorch

Course Information

  • Sessions 2 days
  • Duration 16 hrs
  • Level Beginner
  • Assessment 2 hrs

Venue

12 Woodlands Square #07-85/86/87 Woods Square Tower 1, Singapore 737715. 5 mins walk from Woodlands (NS9) MRT station.

The venue is disabled-friendly.

Skills Framework

TSC Title
Pattern Recognition Systems
TSC Code
ICT-DIT-5026-1.1 TSC
Download Course Brochure

Certification

  • Certificate of Completion from Tertiary Courses - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Completion from Tertiary Courses.
  • OpenCerts from SkillsFuture Singapore - After passing the assessment(s) and achieving at least 75% attendance, participants will receive a OpenCert (aka Statement of Achievement) from SkillsFuture Singapore, certifying that they have achieved the Competency Standard(s) in the above Skills Framework.

WSQ - Building Advanced Machine Learning and AI Solutions with Pytorch

Course Code: TGS-2020505815
  • WSQ
  • SkillsFuture Credit
  • PSEA
  • SFEC
  • Absentee Payroll
  • MCES

4 Review(s) | Add Your Review

What's This Course About

Embark on a groundbreaking journey with our WSQ-endorsed Pattern Recognition with Pytorch course. This course will introduce you to the complexities of recognizing patterns in data sets, utilizing Pytorch as the main framework. Through real-world examples and hands-on projects, you'll get to grips with neural networks, image recognition, and various machine learning algorithms, sharpening your skills in data analysis.

Upon completion of the course, you'll be fully equipped to interpret complex data structures and predict future patterns using Pytorch. This course is your stepping stone to becoming a specialist in machine learning and data analysis, with a particular focus on pattern recognition techniques.

Course Learning Outcomes

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

  • LO1: Assess various machine learning techniques across different application domains.
  • LO2: Apply machine learning techniques to regression and classification problems.
  • LO3: Solve temporal sequential problem using recurrent neural network.
  • LO4: Build pattern recognition systems using convolutional neural network.
  • LO5: Apply machine learning techniques to signal processing.

WSQ Funding

Full Fee $750.00 Before GST
GST $67.50 9% of fee
Baseline Nett $442.50 SG/PR age 21+ · 50% funded
MCES / SME Nett $292.50 SG age 40+ · 70% funded
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 (SFC)

Eligible Singapore Citizens can use their SFC to offset course fee payable after funding but the $4,000 Additional SFC (Mid-Career Support) cannot be used. Click here for SkillsFuture Credit submission

UTAP

Eligible NTUC members can apply for 50% of the unfunded fee from UTAP, capped up to $250/year and for members aged 40 and above, capped up to $500/year. Click here to submit UTAP

PSEA

Eligible Singapore Citizens can use their PSEA funds to offset course fee payable after funding.

To check for Post-Secondary Education Account (PSEA) eligibility for this course, Visit SkillsFuture (course code: TGS-2020505815)

  • Scroll down to “Keyword Tags” to verify for PSEA eligibility.
  • If there is “PSEA” under keyword tags, the course is eligible for PSEA.

Once you are eligible for PSEA, please download and fill up the PSEA Withdrawal Form and email to us.

Course FeeBefore Funding

$750.00 (GST-exclusive)
$817.50 (GST-inclusive)

Course Date

* Required Fields

Additional Note

Please bring your own laptop for hands-on training. If you don't have laptop, we can provide spare laptop for training use.

Post-Course Support

  • We provide free consultation related to the subject matter after the course.
  • Please email your queries to enquiry@tertiaryinfotech.com and we will forward your queries to the subject matter experts.

Cancellation & Reschedule Policy

  • You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commences.
  • We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% for any paid amount.
  • Note the venue of the training is subject to changes due to availability of the classroom.

Course Details

Course Details

What You'll Learn

Topic 1: Overview of Deep Learning Application Domains

  • AI and Deep Learning Landscape
  • Deep Learning Application Domains
  • AI Ethnics

Topic 2: Machine Learning for Regression and Classification

  • General Concepts of Machine Learning and Neural Network (NN)
  • Introduction to Pytorch Framework
  • Build a Regression Model Using NN
  • Build a Classification Model Using NN

Topic 3: Recurrent Neural Network (RNN)

  • Introduction to Recurrent Neural Network (RNN)
  • Build a Temporal Sequential Model Using RNN
  • Build a Sentimental Analysis Model Using RNN

Topic 4: Convolutional Neural Network (CNN)

  • Introduction to Convolutional Neural Network (CNN)
  • Build a Image Classification Model Using CNN
  • Techniques to Resolve Overfitting Issue

Topic 5: Application of Machine Learning to Signal Processing

  • Digital Signal Processing
  • Machine Learning Classification for Signal Processing
  • Evaluation of Signal Processing Performance

Assessment

  • Written Exam
  • Practical Exam

Course Info

Promotion Code

Promo or discount cannot be applied to WSQ courses

Minimum Entry Requirement

Knowledge and Skills

  • Able to operate using computer functions with minimum Computer Literacy Level 2 based on ICAS Computer Skills Assessment Framework
  • Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)

Attitude

  • Positive Learning Attitude
  • Enthusiastic Learner

Experience

  • Minimum of 1 year of working experience.
  • Minimum 18 years old

Minimum Software/Hardware Requirement

Software:

You can download and install the following software:

Hardware: Windows and Mac Laptops

About Progressive Wage Model (PWM)

The Progressive Wage Model (PWM) helps to increase wages of workers through upgrading skills and improving productivity. 

Employers must ensure that their Singapore citizen and PR workers meet the PWM training requirements of attaining at least 1 Workforce Skills Qualification (WSQ) Statement of Attainment, out of the list of approved WSQ training modules.

For more information on PWM, please visit MOM site.

Funding Eligility Criteria

Individual Sponsored Trainee Employer Sponsored Trainee
  • Singapore Citizens or Singapore Permanent Residents of age 21 and above
  • From 1 October 2023, attendance-taking for SWDA's (formerly SSG) funded courses must be done digitally via the Singpass App. This applies to both physical and synchronous e-learning courses.​
  • Trainee must pass all prescribed tests / assessments and attain 100% competency.
  • We reserves the right to claw back the funded amount from trainee if he/she did not meet the eligibility criteria.
  • Singapore Citizens or Singapore Permanent Residents who are DIRECT EMPLOYEE of the sponsoring company.
  • From 1 October 2023, attendance-taking for SWDA's (formerly SSG) funded courses must be done digitally via the Singpass App. This applies to both physical and synchronous e-learning courses.​
  • Trainee must pass all prescribed tests / assessments and attain 100% competency.
  • We reserves the right to claw back the funded amount from the employer if trainee did not meet the eligibility criteria.

 SkillsFuture Credit: 

  • Eligible Singapore Citizens can use their SkillsFuture Credit to offset course fee payable after funding.

 PSEA:

  • To check for Post-Secondary Education Account (PSEA) eligibility, goto mySkillsFuture portal and search for this course code.
  • Scroll down to "Keyword Tags" to verify for PSEA eligibility.
  • If there is “PSEA” under keyword tags, the course is eligible for PSEA.  
  • And if there is no “PSEA” under keyword tags, the course is ineligible for PSEA. 
  • Not all courses are eligible for PSEA funding.

 Absentee Payroll (AP) Funding: 

  • $4.50 per hour, capped at $100,000 per enterprise per calendar year.
  • AP funding will be computed based on the actual number of training hours attended by the trainee.

 SFEC:

  • If the Training Provider has submitted an enrolment for course fee grant claim in Training Partners Gateway (TPGateway), SWDA would be able to derive SFEC funding based on this record. There is no need for enterprise to submit any claim request and the SFEC claim will be automatically generated and disbursed.
  • Where there is no such record, eligible employers are required to submit an SFEC claim after course completion via the SFEC microsite.
  • SkillsFuture Enterprise Credit (SFEC) Microsite 

 

Steps to Apply Skills Future Claim

  • The staff will send you an invoice with the fee breakdown.
  • Login to the MySkillsFuture portal, select the course you’re enrolling on and enter the course date and schedule.
  • Enter the course fee payable by you (including GST) and enter the amount of credit to claim.
  • Upload your invoice and click ‘Submit’

SkillsFuture Level-Up Program

The  SkillsFuture Level-Up Programme provides greater structural support for mid-career Singaporeans aged 40 years and above to pursue a substantive skills reboot and stay relevant in a changing economy. For more information, visit SkillsFuture Level-Up Programme

Get Additional Course Fee Support Up to $500 under UTAP

The Union Training Assistance Programme (UTAP) is a training benefit provided to NTUC Union Members with an objective of encouraging them to upgrade with skills training. It is provided to minimize the training cost. If you are a NTUC Union Member then you can get 50% funding (capped at $500 per year) under Union Training Assistance Programme (UTAP).

For more information visit NTUC U Portal – Union Training Assistance Program (UTAP)

Steps to Apply UTAP

  • Log in to your U Portal account to submit your UTAP application upon completion of the course.

Note

  • SWDA subsidy is available for Singapore Citizens, Permanent Residents, and Corporates.
  • All Singaporeans aged 25 and above can use their SkillsFuture Credit to pay. For more details, visit www.skillsfuture.gov.sg/credit
  • An unfunded course fee can be claimed via SkillsFuture Credit or paid in cash.
  • UTAP funding for NTUC Union Members is capped at $250 for 39 years and below and at $500 for 40 years and above.
  • UTAP support amount will be paid to training provider first and claimed after end of class by learner.

Appeal Process

  1. The candidate has the right to disagree with the assessment decision made by the assessor.
  2. When giving feedback to the candidate, the assessor must check with the candidate if he agrees with the assessment outcome.
  3. If the candidate agrees with the assessment outcome, the assessor & the candidate must sign the Assessment Summary Record.
  4. If the candidate disagrees with the assessment outcome, he/she should not sign in the Assessment Summary Record.
  5. If the candidate intends to appeal the decision, he/she should first discuss the matter with the assessor/assessment manager.
  6. If the candidate is still not satisfied with the decision, the candidate must notify the assessor of the decision to appeal. The assessor will reflect the candidate’s intention in the Feedback Section of the Assessment Summary Record.
  7. The assessor will notify the assessor manager about the candidate’s intention to lodge an appeal.
  8. The candidate must lodge the appeal within 7 days, giving reasons for appeal 
  9. The assessor can help the candidate with writing and lodging the appeal.
  10. he assessment manager will collect information from the candidate & assessor and give a final decision.
  11. A record of the appeal and any subsequent actions and findings will be made.
  12. An Assessment Appeal Panel will be formed to review and give a decision.
  13. The outcome of the appeal will be made known to the candidate within 2 weeks from the date the appeal was lodged.
  14. The decision of the Assessment Appeal Panel is final and no further appeal will be entertained.
  15. Please click the link below to fill up the Candidates Appeal Form.

Job Roles

Job Roles

  • Data Scientist
  • Machine Learning Engineer
  • Statistician
  • R Developer
  • Quantitative Researcher
  • Bioinformatics Scientist
  • Predictive Modeler
  • Data Analyst (focusing on advanced analytics)
  • Big Data Specialist (using R)
  • Algorithm Developer
  • AI Researcher (using R)
  • Financial Quantitative Analyst
  • Business Intelligence Specialist (with R expertise)
  • Marketing Analytics Specialist (using R)
  • Epidemiologist (utilizing machine learning).

Trainers

Trainers

Yeo Hwee Theng is a data science leader and AI strategist with extensive experience in driving enterprise analytics, AI adoption, and data architecture initiatives across healthcare, finance, and government sectors. As the Data & Analytics Product Lead at Amplify Health, she leads large-scale data transformation and machine learning projects focused on improving business outcomes through data-driven decision-making. Her previous roles include AI & Data Architect at Huawei International and Senior Data Scientist at DataRobot, where she implemented advanced AI and analytics solutions across the Asia-Pacific region. She holds a Master of Technology in Enterprise Business Analytics from the National University of Singapore and an Advanced Certificate in Learning and Performance (ACLP).
Teh Siew Yee is an experienced adult educator and corporate trainer specializing in business communication, workplace effectiveness, and professional development. With years of experience across both corporate and training environments, she has helped learners enhance their skills in problem-solving, collaboration, and interpersonal communication. Her ability to translate complex concepts into clear, practical strategies ensures that participants can immediately apply their learning in the workplace. As an ACLP-certified trainer, Siew Yee delivers WSQ courses with a strong focus on learner engagement and workplace application. She integrates case studies, role-plays, and reflective exercises into her sessions, ensuring participants develop not only knowledge but also confidence in real-world contexts. By combining her corporate experience with adult education expertise, she empowers learners to improve workplace efficiency, strengthen teamwork, and achieve personal and organizational success.

Dr Alvin Ang is an ACLP-certified trainer with a Ph.D. in Operations Research from Nanyang Technological University and over a decade of academic and industry experience in data science, AI, and optimization. He has taught at NTU, SUSS, Curtin University, and SP Jain School of Global Management, and also served as an IBM Data Science Instructor. With certifications in TensorFlow, PyTorch, NLP, and deep learning, Dr Ang brings both research depth and practical application into his teaching.
In his PyTorch training, Dr Ang emphasizes hands-on learning in building advanced machine learning and AI models. His sessions guide learners through neural networks, deep learning workflows, and applied projects, ensuring they gain both theoretical knowledge and practical skills. By combining academic rigor with case-based teaching, he empowers participants to design and implement AI solutions with real-world impact.

CY Quah is an ACLP-certified trainer and data science professional with extensive experience in Python, NLP, and machine learning. He has led AI training programs for SAP, Temasek Polytechnic, and IMDA under the SGUnited Mid-Career Pathways initiative, and has delivered corporate workshops on text analytics, recommender systems, and chatbot development. His expertise includes applying NLP tools such as NLTK, spaCy, and Gensim for sentiment analysis, topic modeling, and text classification.
Terence Ee is an experienced IT leader and consultant with more than 25 years of expertise in technology management, information systems, and digital transformation. He has served as Chief Information Officer at the Supreme Court of Singapore and Vice President of Information Systems at Senoko Energy, where he led major IT modernization projects. Since 2017, he has worked as an independent consultant and ACLP-certified trainer, specializing in guiding SMEs and enterprises in adopting future-ready digital platforms. As a WSQ-accredited trainer, Terence delivers programs in digital collaboration, IT governance, and productivity tools. His facilitation emphasizes case studies, simulations, and hands-on practice, enabling learners to apply modern IT systems such as Microsoft 365 and Google Workspace to improve collaboration and business efficiency. With his leadership background and deep IT expertise, Terence prepares learners to thrive in digitally transforming environments.

Review

Customer Reviews (4)

will recommend Review by Course Participant/Trainee
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2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
. (Posted on 3/5/2024)
will recommend Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
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Would be nice if students have access to Google Colab Pro for smoother practical sessions. Current lessons operate on Colab Free Plan which limits hardware resources, slowing down processing of Python scripts on the online Jupyter Notebook platform in Colab. (Posted on 3/5/2024)
will recommend Review by Course Participant/Trainee
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Great that you provide laptop! Thank God (Posted on 3/5/2024)
will recommend Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
. (Posted on 7/18/2021)

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