JavaScript seems to be disabled in your browser.
You must have JavaScript enabled in your browser to utilize the functionality of this website.

Home
WSQ - AI Application Development with Large Language Models (LLM)

WSQ - AI Application Development with Large Language Models (LLM)

16 Review(s) | Add Your Review

Dive into the innovative world of AI Application Development with Large Language Models (LLM) in this comprehensive course. Designed for those looking to enhance their digital marketing expertise, the course focuses on developing practical skills for formulating and budgeting effective social media strategies. You'll learn how to align these strategies with organizational standards and market needs, ensuring a robust online presence. The course emphasizes the use of AI and large language models in analyzing customer behavior, providing insights into creating impactful digital content that resonates with your audience.

In addition to understanding the operational aspects, the course provides a deeper exploration into the evaluation of digital marketing technologies on Meta platforms. This includes an in-depth look at tools and techniques for managing social media, understanding customer behavior, and planning communication effectively. The course also delves into the intricacies of synthesizing market trends, incorporating a keen understanding of privacy and copyright laws, and how they influence social media marketing strategies. By the end of the course, participants will be equipped with the knowledge and skills to leverage AI in crafting cutting-edge digital marketing strategies that drive engagement and business growth.

Learning Outcomes

By end of the course, learners should be able to:

Analyze AI applications using large language models (LLM)
Establish LLM algorithm methodologies with word embedding and vector databases
Identify and evaluate strengths, limitations of LLM applications, and effectiveness in various tasks.
Assess LLM application feasibility in product development using function calling and langchain.
Evaluate and finetune LLM models for application improvement

Course Brochure

Download WSQ - AI Application Development with Large Language Models (LLM) Brochure

Skills Framework

This course follows the guideline of Artificial Intelligence Application in Product Development ICT-TEM-4034-1.1 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
$800	$72.00	$472.00	$312.00

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

Course Code: TGS-2024042309

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.

Course Cancellation/Reschedule Policy

You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commerce.
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

Topic 1 Fundamental of Large Language Model (LLM)

What are LLMs
Applications and use cases of LLMs
Create a custom GPTs application from scratch
Overview of Transformer architecture
Self-attention mechanism
Comparison of popular LLM Models

Topic 2 Word Embedding and Vector Databases

Word embedding
Similarity and correlation of words
Vector databases

Topic 3 Evaluating LLM Tasks

NER
Translation
Summarization
Text Generation
Question Answering
Retrieval Augmented Generation (RAG)

Topic 4 Introduction to Function Calling and Langchain

OpenAI Function Calling
Langchain Components, Tools and Agents

Topic 5 Fine Tuning LLM Models

Why fine tuning LLM models
Training and evaluation of fine-tuned LLM models

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.

Target Age Group: 21 to 65 years old

Minimum Software/Hardware Requirement

Software:

Download and Install the following software

Hardware: Windows or 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
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

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
AI Specialist
Research Scientist
Software Engineer
Information Technology Consultant
Data Analyst
Business Analyst
Systems Analyst
Project Manager
Product Manager
Technical Lead
AI Architect
Data Engineering Manager
Chief Technology Officer

Trainers

Teh Siew Yee: Teh Siew Yee is a seasoned leader in data science and digital transformation, with over 20 years of experience driving organisational strategy, talent development, and the design of data ecosystems across Asia Pacific and global markets. He has successfully led cross-geographical teams and collaborated with industry leaders from the US, UK, China, India, Japan, South Korea, Australia, and beyond, focusing on leveraging data to achieve business objectives and optimize operations.

With expertise spanning predictive modeling, machine learning, deep learning, and IoT, he has hands-on experience in data architecture, engineering, and analytics. He has also developed comprehensive training programs, equipping all levels of an organisation— from C-suite to working-level employees— with the skills needed for digital transformation. His industry experience covers sectors such as tech, education, finance, aerospace, and eCommerce, making him a sought-after expert in data-driven business strategy.

Solomon Soh Zhe Hong: Solomon is ACTA certified and has trained and coached over 100 professionals in the area of data science, python programming and coding. Solomon is a Certified AI Engineer Associate by AI Singapore and holds certifications in Alibaba Cloud Architect and Alteryx respectively. Solomon interests include Reinforcement Learning, Natural Language Processing and Time-Series analysis.

Alfred Yap Swee Leong: Alfred Yap is an ACLP certified trainer with strong financial and shopper marketing domain background and extensive experience in information technology. In addition, he is both an IBM certified Cloud Computing Practitioner and an IBM Enterprise Design Thinking Practitioner.
Alfred Yap has spent decades teaching adult learners since the 90s. Kickstarting his teaching career as a trainer for Oracle University. Thereafter, he has had vast experience conducting ICT related training to various companies in the Consulting, Media, and Training industry.
Alfred Yap earned his undergraduate degree from USF, America and master degree from NTU, Singapore majoring in Knowledge Management. His current interests include Cyber Security, Cloud computing and Blockchain.