Key Takeaways
At the end of the course, the participants will be able to:
- Differentiate MLSecOps and traditional DevSecOps in terms of objectives, characteristics, challenges, approaches.
- Design and evaluate the pipeline of a ML model and its operational data by leveraging MLSecOps platforms and best practices.
- Architect the scaling of ML with Cloud & MLSecOps Platforms.
- Differentiate LLMSecOps and MLSecOps including the deployment strategies.
- Design and evaluate the pipeline and conduct the tasks of the pipeline of LLM and its operational data by leveraging on LLMSecOps platforms and best practices.
Who Should Attend
This course is applicable for:
- Data Scientists
- AI and ML Engineers
- DevOps Engineers
- Software Engineers who are part of a deployment team which facilitates a complete end-to-end process spanning from development to production
Pre-requisites
Participants should have some knowledge of DevSecOps.
What to Bring
No printed copies of course materials are issued.
Participants must bring their laptops (participants will not be able to complete the workshop with their tablets) with power charger to access and download course materials.
If you are bringing a laptop, please see below for the tech specs:
| Minimum | Recommended |
Computer and processor | 1.6 GHz or faster, 2-core Intel Core i3 or equivalent | 1.8 GHz, 2-core Intel Core i3 or equivalent |
Memory | 4 GB RAM | 8 GB RAM |
Hard Disk | 256 GB disk size | |
Display | 1280 x 768 screen resolution (32-bit requires hardware acceleration for 4K and higher) | |
Graphics | Graphics hardware acceleration requires DirectX 9 or later, with WDDM 2.0 or higher for Windows 10 (or WDDM 1.3 or higher for Windows 10 Fall Creators Update). | DirectX 10 graphics card for graphics hardware acceleration |
Others | An internet connection – broadband wired or wireless Speakers and a microphone – built-in or USB plug-in or wireless Bluetooth A webcam or HD webcam - built-in or USB plug-in |
|
What Will Be Covered
- The process of architecting AI solutions that incorporate AI agents.
- The applications of different types of AI agents.
- The reference architectures for building agentic AI solutions.
- The use of agent frameworks for building agentic AI solutions.
- Advanced SE architecture and design techniques for integrating intelligent components.
Fees & Subsidies
Fees for 2024
| |
Full Fee |
Singaporeans & PRs
(self-sponsored) |
| Full course fee |
S$2700 |
S$2700 |
| ISS Subsidy |
- |
(S$270) |
| Nett course fee |
S$2700 |
S$2430 |
| 9% GST on nett course fee |
S$243 |
S$218.70 |
| Total nett course fee payable, including GST |
S$2943 |
S$2648.70 |
Note:
- All fees and subsidies are valid from January 2024, unless otherwise advised.
- 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.
- From 1st January 2024, the GST will be increased to 9%.
Certificate
The NUS-ISS Certificate of Completion will be issued to participants who have attended at least 75% of the course and passed the required assessments.
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.