Course Content
- Classic DNN Models: Dive into the fundamentals of Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Long Short-Term Memory (LSTM) networks. Understand their applications in language tasks and learn how to build recognition models.
- Attention & Transformer: Uncover the secrets of attention mechanisms and the revolutionary Transformer architecture.
- Sequence-to-Sequence & Encoder-Decoder Framework: Explore the magic behind sequence-to-sequence models and how they enable tasks like machine translation and summarisation.
- Transfer Learning with Pretrained LLMs: Get hands-on experience with BERT, GPT, and T5. Learn how to leverage their pretraining for downstream tasks.
- Fine-Tuning LLMs (Bloom/LLaMa/Gemma): Master the art of fine-tuning large language models. Understand model tuning with prompts and achieve parameter-efficient fine-tuning.
You will gain practical experience through scenario-based case studies and hands-on sessions using popular libraries such as NLTK, skLearn, Gensim, spaCy, and LLM-based toolkits.
This course is part of the Artificial Intelligence, Data Science and Graduate Certificate in Practical Language Processing Series offered by NUS-ISS.
Key Takeaways
- Gain proficiency in classic DNN models, including CNNs, RNNs, LSTMs, and GRUs, setting the stage for advanced language processing.
- Navigate cutting-edge frameworks like sequence-to-sequence models and transformer architectures.
- Explore the true potential of Large Language Models through fine-tuning LLMs like Bloom and LLaMa, and probing advanced topics like emergent phenomena, hallucination, and Retrieval Augmented Generation.
Who Should Attend
- Data Scientists & Engineers: Enhance your skills in language processing with the latest deep learning techniques.
- Analysts & Researchers: Learn to use advanced tools for in-depth analysis of text data.
- Technology Enthusiasts: Stay at the forefront of technology by exploring the limitless possibilities of language processing with DL and LLMs.
Prerequisites
Possess foundational knowledge in text processing and predictive modelling with text data (at the level of Text Analytics course offered by NUS-ISS).
Strong programming skills using Python and familiar with packages like Numpy, Pandas and Scikit-Learn.
Well-versed with Anaconda, Jupyter Notebooks, Google Colab and Github.
Course Logistics
- No Printed Materials: Course materials are accessed digitally. Do kindly note that no printed copies of course materials will be issued.
- Device Requirements: Bring an internet-enabled device (laptop, tablet, etc) with power chargers to access and download course materials.
If you are bringing a laptop, kindly refer to the table below for the recommended tech specs:
|
|
Minimum
|
Recommended
|
|
Operating Systems
|
• Windows 7 above
• Mac OS
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Laptop running the latest
version of either Windows or
Mac OS
|
|
System Type
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32-bit
|
64-bit
|
|
Memory
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8 GB RAM
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16+ GB RAM
|
|
Hard Drive
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256 GB disk size
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|
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Others
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• An internet connection – broadband wired or wireless
• Installation permissions (non-company laptops)
• Keyboard
• Mouse/Trackpad
• Display
• Power adapter (laptop battery might run out) |
DirectX 10 graphics card for graphics hardware acceleration
|
Fees & Subsidies
SkillsFuture Singapore (SSG) Funding 2026 (Effective 1 July)
| Fee Component | Full Course Fees | Singapore Citizens & PRs Aged 21 Years and Above (70% Funding Support) | Singapore Citizens Aged 40 Years and Above (90% Funding Support) | Enhanced Training Support for SMEs (ETSS) (90% Funding Support) |
|---|
| Full Course Fee | S$3,800.00 | S$3,800.00 | S$3,800.00 | S$3,800.00 |
| SSG Funding | - | S$2,660.00 | S$2,660.00 | S$2,660.00 |
| Nett Course Fee | S$3,800.00 | S$1,140.00 | S$1,140.00 | S$1,140.00 |
| 9% GST on Nett Course Fee | S$342.00 | S$102.60 | S$102.60 | S$102.60 |
| Additional Funding if Eligible Under Various Schemes | - | - | S$760.00 | S$760.00 |
| Total Nett Course Fee Payable, Including GST | S$4,142.00 | S$1,242.60 | S$482.60 | S$482.60 |
|---|
Note:
- SSG Funding is available to qualified individuals, subject to meeting the attendance requirement and passing of assessment.
- All self-sponsored Singaporeans aged 25 and above can use their SkillsFuture Credit to pay for course fees. For more information about SkillsFuture Credit, click here.
- SME fees are applicable only to participants who are sponsored by small and medium enterprises.
- SSG funding is subjected to availability.
Certificate
Certificate of Completion
Participants have to meet a minimum attendance rate of 75% and are required to pass the assessment to be issued a Certificate of Completion.
Join Us
Elevate your text processing capabilities. Register now to harness the potential of DL and LLMs.
Preparing for Your Course
NUS-ISS Course Registration Terms and Conditions
Find out more.
NUS-ISS and Learner’s Commitment and Responsibilities
Find out more.
WIFI Access
WIFI access will be made available to participants.
Venue
NUS-ISS
25 Heng Mui Keng Terrace
Singapore 119615
Click HERE for directions to NUS-ISS
In the event of a change of venue, participants are advised to refer to the acceptance email sent one week prior to the commencement date.
Course Confirmation
All classes are subject to confirmation and NUS-ISS will send an acceptance email to participants one week prior to the commencement date. Confirmed registrants are to attend and complete all lectures, class exercises, workshops and assessments (where applicable). Additionally, all responses to feedbacks and surveys conducted by NUS-ISS and its partners must be submitted. All training and assessments will be delivered as described in the course webpage.
General Enquiry
Please feel free to write to ask-iss@nus.edu.sg if you have any enquiry or feedback.