Dates:
Operating System: To be advised
Networking: To be advised
Course Objectives
This Professional Certificate will equip learners with the following competencies:
- Synchronization
- Deadlock
- Basic Memory Management
- Virtual Memory
- File Systems
- File System Case Studies
- Introduction to Computer Networking
- Application Layer: HTTP and DNS
- Transport Layer: Reliable Protocol Design, TCP, UDP
- Network Layer: DHCP, IP, ARP, Routing
- Link Layer: Multiple Access Protocols, Ethernet, Multiplexing, Switching
- Physical Layer: Signaling, Modulation
Job Role Readiness
It will prepare learners in the following job roles to perform their responsibilities more effectively/ It will prepare learners for the following job roles:
- Data / AI / System / Software Engineers
Programme Structure
Who Should Attend
Data / AI / System / Software Engineers
Prerequisites
- STEM field degree/ poly diploma
- A-Level with reasonable math/computing grade
Course Conveners
(Click their photos to view their short biographies)
Dr Jithin Vachery
Dr Jithin Vachery
Jithin Vachery is a Lecturer at the School of Computing, NUS, Singapore. Prior to this, he was a Postdoctoral Research Fellow working with Prof. Mohan S Kankanhalli in the N-CRiPT lab. His current research is focused on social network analysis. He obtained his PhD from the Computer Science Department at the Indian Institute of Technology, Madras, under the guidance of Prof. Sayan Ranu in the AIDB Lab, IIT-M. His thesis is focused on searching and optimization on graphs. Before joining IIT-M, he obtained his Master of Engineering degree in Computer Science and Engineering from the Computer Science and Automation Department at the Indian Institute of Science, Bangalore, India, where he worked with Prof. Ambedkar Dukkipati in the area of Information Theory.
Assoc Prof Wong Weng Fai
Assoc Prof Wong Weng Fai
Assoc Prof Wong Weng Fai works in the systems area with particular interest in the interface between the hardware and software stacks, and how they can be mutually co-optimized. He has worked on optimizing software and applications for novel hardware including FPGAs, GPUs, non-volatile memory, and specialized bus interfaces. These days, his focus is on approximate computing, including precision analysis, variable precision arithmetic, and approximation of deep learning networks using approximate hardware accelerators.
Course Fees
Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes
Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.
To enquire, email soc-ace@nus.edu.sg
To register, click Register
Course Codes
Operating System: TGS- 2022012331 (Classroom Learning) / TGS- 2022012302 (Synchronous e-learning)
Networking: TGS- 2022012340 (Classroom Learning) / TGS- 2022012269 (Synchronous e-learning)