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Enhance Your Employability with Certified Skills and Courses in Singapore - WSQ , IBF-STS, Skills Certification

WSQ - Pattern Recognition and Machine Learning with R

Dive into the intricate world of pattern recognition and machine learning with our WSQ-accredited course. This course is structured to take you from the essentials of R programming to the complexities of machine learning algorithms. You will learn to deploy pattern recognition techniques for data classification, delve into clustering methods, and explore predictive analytics. Real-world examples and projects are integrated into the curriculum for hands-on learning.

Whether you're a seasoned data scientist or a beginner eager to expand your skill set, this course is designed to equip you with the knowledge needed for the evolving field of data analytics. You'll leave with practical experience in applying machine learning algorithms using R, positioning you at the forefront of today’s data-driven landscape. Upgrade your analytics skills and stay ahead of the curve with our specialized training.

Learning Outcomes

By end of the course, learners should be able to

  • Model pattern recognition problems suitable for machine learning.
  • Apply supervised regression techniques to predict pattern in the data.
  • Apply supervised classification techniques to classify pattern in the data.
  • Apply unsupervised clustering techniques to cluster patterns and detect anomaly in the data.
  • Apply principal component analysis as alternative method to detect pattern in the data.
  • Apply deep neural network and CNN models for visual recognition.

Course Objectives

  • Learners will be able to derive useful hidden pattern in the data using machine learning methods.

Course Brochure

Download WSQ - Pattern Recognition and Machine Learning with R Brochure

Skills Framework

This course follows the guideline of Pattern Recognition Systems ICT-DIT-4026-1.1 TSC under ICT Skills Framework

Certification

  • Certificate of Completion from Tertiary Infotech - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Completion from Tertiary Infotech.

  • 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 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 2024
Full Fee GST Nett Fee after Funding (Incl. GST)
Baseline MCES / SME
$750.00 $67.50 $442.50 $292.50

Baseline: Singaporean/PR age 21 and above
MCES(Mid-Career Enhanced Subsidy): S'porean age 40 & above

Upon registration, we will advise further on how to tap on the WSQ Training Subsidy.


You can pay the nett fee (after the WSQ training subsidy) by the following :

SkillsFuture Enterprise Credit (SFEC)

Eligible Singapore-registered companies can tap on $10000 SFEC to cover 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. Please inform us if you intend to use your PSEA funding.

To check for Post-Secondary Education Account (PSEA) eligibility for this course, Visit SkillsFuture (course code: TGS-2020504357)
  • Scroll down to “Keyword Tags” to verify for PSEA eligibility.
  • If there is “PSEA” under keyword tags, the course is eligible for PSEA.
Course Code: TGS-2020504357

Course Booking

The course fee listed below is before subsidy/grant, if applicable. We will apply for the grant and send you the invoice with nett fee.

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

Course Date

* Required Fields

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 and get back to you asap.

Course Cancellation/Reschedule Policy

We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% to participants.
Note the venue of the training is subject to changes due to class size and availability of the classroom.
Note the minimal class size to start a class is 3 Pax.


Course Details

Topic 1: Overview of Machine Learning

  • Introduction to Machine Learning
  • Pattern Recognition Problems Suitable for Machine Learning
  • Supervised vs Unsupervised Learnings
  • Types of Machine Learning
  • Machine Learning Techniques
  • R Packages for Machine Learning

Topic 2: Regression

  • What is Regression
  • Applications of Regression
  • Least Square Error Minimization
  • Data Pre-processing
  • Bias vs Variance Trade-off
  • Regression Methods with Regularization
  • Logistic Regression

Topic 3: Classification

  • What is Classification
  • Applications of Classification
  • Classification Algorithms
  • Confusion Matrix
  • Classification Performance Evaluation

Topic 4: Clustering

  • What is Clustering
  • Applications of Clustering
  • Distance Measure
  • Clustering Algorithms
  • Clustering Performance Evaluation
  • Anomaly Detection Problem

Topic 5: Principal Component Analysis

  • • Principal Component Analysis (PCA) and Dimension Reduction
  • • Applications of PCA
  • • PCA Workflow

Topic 6: Deep Learning

  • What is Neural Network
  • Activation Functions
  • Loss Function Minimization
  • Gradient Descent Algorithms and Learning Rate
  • Deep Neural Network for Visual Recognition
  • Improve Visual Recognition with Convolutional Neural Network
  • The Future of AI
  • AI Ethics

Final Assessment

  • Written Assessment - Short Answer Questions (WA-SAQ)
  • Practical Performance (PP)

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

Software Requirement

Please download and install the following software prior to the class

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 SkillsFuture Singapore's (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 SkillsFuture Singapore's (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), SSG 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

  • SSG 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.

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

Dwight Nuwan Fonseka: Dwight Nuwan Fonseka is a ACLP certified trainer. He have a degree in Biotechnology from NUS ,Advanced diploma in Pharmaceutical management from MDIS and Masters in Education from NTU. He have 8 years experience of teaching biology at O and A levels/ IB level in international schools in Singapore and overseas.

Dr Alvin Ang: Dr Alvin Ang is a ACTA certified trainer. Alvin Ang did his Ph.D., Masters and Bachelors from NTU, Singapore. Previously he was a Principal Consultant (Data Science) as well as an Assistant Professor. He was also 8 years SUSS adjunct lecturer. His focus and interest is in the area of real world data science. Though an operational researcher by study, his passion for practical applications outweigh his academic background. He owns a startup externally

Khoo Yong: Khoo Yong is a ACTA certified trainer. Khoo Yong graduated from NTU with a bachelor degree in Mechanical and Production Engineering. Currently, working as a principal engineer in one of the top 3 Semiconductor Manufacturing Pure-Play Foundry in the world, he is a statistician support Operations and Engineering, driving the Statistical Process Control Program in the Fab. He specializes in Statistics , basic Excel and advance Excel, including excel macro coding. He regularly conduct Statistical Process Control Courses in the company. He is a certified Black Belt.

Customer Reviews (4)

The instructor Mr Dwight was really helpful and engaging, thank you :) 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
Perhaps having more examples and datasets to try out, going deeper into the mathematical and statistical concepts (Posted on 5/22/2023)
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
Trainer is very experienced and knowledgeable and generous in sharing his knowledge (Posted on 5/11/2023)
might 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
Learnt a lot but just too much info in 2 days. (Posted on 5/11/2023)
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 2/3/2023)

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