Bachelor of Engineering (Hons) in Computer Engineering with a Second Major in Data Analytics

Single Degree with 2nd Major

This Bachelor of Engineering (Hons) in Computer Engineering with a Second Major in Data Analytics programme provides a strong foundation in both computer hardware and software design and equips students with essential skills in data analytics. The combination is increasingly valuable in a data-driven world, enabling graduates to design and build computational systems and, at the same time, extract meaningful insights from large, complex datasets. This interdisciplinary program is jointly offered by NTU's College of Computing and Data Science (CCDS) and the College of Engineering (CoE). 

This programme combines hardware-focused engineering with advanced data analytics and machine learning. Students learn to design and optimise computational systems through data-driven insights, gaining hands-on experience across the entire data lifecycle—from collection and processing to analysis and visualisation. The result is a new generation of engineers ready to drive innovation in AI, robotics, embedded systems, and FinTech.

GCE ‘A’ Level

Pass in H2 Level Mathematics, and

Pass in H2 Level Biology/Chemistry/Computing/Physics, and

Pass in H1 Level/‘O’ Level Physics* or equivalent.

 

International Baccalaureate

Pass in HL Mathematics, and

Pass in HL Biology/Chemistry/Computer Science/Physics, and

Pass in SL Physics** or equivalent.

 

NUS High School Diploma

Major CAP of 2.0 in Mathematics, and

Major CAP of 2.0 in Biology/Chemistry/Physics, and

Overall CAP of 2.0 in Physics" or equivalent.

 

Course exemptions:
Polytechnic Exemptions

 i) 27 AUs of exemptions and they are: 

a. Technical Elective 1 (Major Prescribed elective, to be taken from CZ4xxx courses) - 3 AUs 

b. Technical Elective 2 (Major Prescribed elective, to be taken from CZ4xxx courses) – 3 AUs 

c. GER PE (BM, LA) - 6 AUs 

d. Unrestricted electives - 15 AUs 

ii) Additional 3 AUs in Technical Elective 3 (Major Prescribed elective, to be taken from CZ4xxx courses) or other relevant courses on a case-by-case basis subject to the students having participated and done well in NTU research or other projects, or with additional Certificate in Mathematics from Diploma-Plus programmes, or having taken and done well in university level courses. 

iii) CE1103 Introduction to Computational Thinking and Programming (Core)*#– 3 AUs 

* For students who pass the exemption test. More details on this test will be disseminated to eligible students via their NTU email after matriculation. 

# Not applicable to all diplomas. Some examples are: 

- Diploma in Aerospace Engineering from Temasek Polytechnic 

- Diploma in Aerospace Electronics from Temasek Polytechnic 

- Diploma in Engineering with Business from Singapore Polytechnic

 

International & Other Qualifications

Pass in Senior High School Level Mathematics, and

Pass in Senior High School Level Biology/Chemistry/Physics,

and

Pass in Junior High School Level Physics^^

 

Diploma Holders

Applicants should have a relevant diploma from one of the local polytechnics and those with a Certificate of Merit, Diploma with Merit or Diploma with Distinction may apply for any programme in NTU.

For the list of acceptable local diplomas and exempted courses, please visit here

*Pass in H1 Level or ‘O’ Level Physics is only applicable to applicants who have not read H2 Level Physics.

**Pass in SL Physics is only applicable to applicants who have not read HL Physics.

"Overall CAP of 2.0 in Physics is only applicable to applicants who have not majored in Physics.

^^Pass in Junior High School Level Physics is only applicable to applicants who have not read Senior High School Level Physics

Course Duration : 4 Years

Kindly view Programme Structure under Our Brochure Here


View Curriculum here

Graduates are well-equipped for high-demand roles that blend strong engineering expertise with advanced data analytics. They can take on data-focused positions such as Data Scientist, Business Intelligence Developer, Data Analyst, or Data Architect—designing data systems, uncovering insights, and building predictive models. Those drawn to engineering can excel as Embedded Systems Engineers, Hardware-Software Architects, or R&D Engineers, applying data-driven approaches to enhance system design and efficiency. The programme also opens doors to emerging fields like AI, Machine Learning, and FinTech, where computing and analytics intersect. Beyond technical paths, graduates are well-prepared for consulting, innovation, and entrepreneurship, using data insights to shape technology strategies or launch their own ventures.

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