Dates:
Data Structure and Algorithm Part I:
To be advised
Data Structure and Algorithm Part II:
To be advised
Duration: 6 Days
Course Objectives
This Professional Certificate will equip learners with the following competencies:
- Algorithm Analysis Complexity
- Recursion
- Advanced Sorting & Searching
- Abstract Data Type, List ADT, Linked List & Variations
- Stack ADT and Queue ADT
- Tree, Binary Tree, BST ADT
- Self-Balanced BST ADT
- Heap & Priority Queue ADT
- Hash Table ADT
- Graph Introduction and basic representations
- Advanced Graph I
- Advanced Graph II
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
Participants need to meet one of the following:
- STEM field degree/ poly diploma
- A Level with reasonable math / computing grade
- Basic programming background
Course Convener
(Click their photos to view their short biographies)
Assoc Prof Soo Yuen Jien
Assoc Prof Soo Yuen Jien
Assoc Prof Soo Yuen Jien has been in NUS for more than 20 years. He received the B.Sc., M.Sc. and Ph.D degree from NUS in year 2000, 2001 and 2006 respectively.
Starting off as a teaching assistant in year 2000, he has since enjoyed teaching for 10 plus years. Yuen Jien is now an Associate Professor in Computer Science Department of School of Computing.
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
Data Structure and Algorithm Part I: TGS-2022012314 (Classroom Learning) / TGS-2022012336 (Synchronous e-learning)
Data Structure and Algorithm Part II: TGS-2022012337 (Classroom Learning) / TGS-2022012338 (Synchronous e-learning)