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[NP-SGAI-22] LLM Application - Part of Post Diploma Certificate in Deep Learning and Applied Generative AI (SDGAI)

Offered by School of InfoComm Technology

Specialist Diploma

About Course
Course Schedule
Course Structure
Entry Requirements
Financial Matters
Register Interest
Area of interest
Artificial Intelligence, Technology

About Course

Course Objectives

This module introduces the fundamentals of sequential generative models to create or generate new text content. Learners will explore Generative AI models such as Large Language Model (LLM), LangChain, Generative Pre-Training (GPT) and more that are commonly used to understand and generate text. There will be opportunities for learners to experience the practical applications of these models in text processing. Adopting an experiential learning approach, learners will implement the Generative AI models by coding with associated libraries.

Course Description

LLM Application - Part of Post Diploma Certificate in Deep Learning and Applied Generative AI (SDGAI) is a 37.5 hrs module.

Course 
Schedule

Classes Day: Every Mon or Thurs
Time: 6pm to 10.30pm
Mode of training: Classroom, Synchronous eLearning

Recommended that learners have prior knowledge of Python programming before enrolling in other modules. If learners do not have a background in Python programming, they are encouraged to take Programming for Analytics first.

Course Structure

TPG course reference No.

TGS-2023038932

LLM Application - Part of Post Diploma Certificate in Deep Learning and Applied Generative AI (SDGAI)
LLM Application (NP-0624LLLMA)
This module introduces the fundamentals of sequential generative models to create or generate new text content. Learners will explore Generative AI models such as Large Language Model (LLM), LangChain, Generative Pre-Training (GPT) and more that are commonly used to understand and generate text. There will be opportunities for learners to experience the practical applications of these models in text processing. Adopting an experiential learning approach, learners will implement the Generative AI models by coding with associated libraries.

Entry Requirements

Condition 1

Highest qualification

Polytechnic Diploma
or

Condition 2

Highest qualification

Bachelor's Or Equivalent
or

Condition 3

Working experience

Full-time; Duration: 1 year

Financial matters

Course fees payable (incl. GST & excl. supplementary fee)

Description LLM Application - Part of Post Diploma Certificate in Deep Learning and Applied Generative AI (SDGAI) Total course fee
Full Course fee $1,242.60 $1,242.60
PR Sponsored by SME $144.78 $144.78
Singapore Citizen Sponsored by SME $144.78 $144.78
Singapore Citizen Aged 40 & Above $144.78 $144.78
Long-Term Visit Pass Plus $372.78 $372.78
Singapore PR $372.78 $372.78
Singapore Citizen Aged Below 40 $372.78 $372.78

GST rate

The course fees payable above are inclusive of 9% GST rate.

Payment option

The first payment needs to be made after accepting the offer.

Allowed payment by

The course fee allows to be paid by:
Post-Secondary Education Account (Adhoc withdrawal form);
SkillsFuture Credits (SFC);
Credit card (e-payment);
Debit card (e-payment);
PayNow (e-payment).

Important note: All course fees are determined based on prevailing funding policies and subject to review and revision annually.

Nett Supplementary Fees Payable

  • GPA Insurance Fee S$2.11,subject to GST,fees payable S$2.30 Allow payment by Post-Secondary Education Account (Adhoc withdrawal form); Allow payment by Post-Secondary Education Account (Standing order form)
  • Other Fees S$7.43,subject to GST,fees payable S$8.10 Allow payment by Post-Secondary Education Account (Adhoc withdrawal form); Allow payment by Post-Secondary Education Account (Standing order form)

Refund and withdrawal policy

  • Please note that a 100% refund will be available if the withdrawal request is submitted more than or equal to 14 days before the course start date.
  • Please note that a 50% refund will be available if the withdrawal request is submitted less than 14 days before the course start date.
  • Please note that no refund will be available if the withdrawal request is submitted on or after the course start date.