Bachelor of Engineering (Honours)(Civil)/Master of Data Science

5 Years On Campus Bachelors Program

Queensland University of Technology

Program Overview

The Bachelor of Engineering (Honours) (Civil Engineering) / Master of Data Science at Queensland University of Technology is an advanced double degree that blends civil engineering expertise with high-level data science and analytics skills. It is designed for students who want to build infrastructure while also using data, artificial intelligence, and modelling to solve complex real-world problems.

Curriculum Structure

Year 1

In your first year, you develop core foundations in engineering, mathematics, and computing. You’ll study units such as Engineering Mathematics, Introduction to Civil Engineering, Programming Principles, and Data Fundamentals, building strong analytical and technical skills from both disciplines.

Year 2

The second year strengthens your engineering and data science base. You’ll explore Structural Mechanics, Fluid Mechanics, Statistics and Probability, and Object-Oriented Programming, learning how engineering systems and data analysis methods work together.

Year 3

In year three, learning becomes more applied and integrated. Units such as Geotechnical Engineering, Transportation Engineering, Database Systems, and Data Analytics Methods help you apply computational tools to real infrastructure and engineering challenges.

Year 4

This year focuses on advanced civil engineering design and data-driven problem solving. You’ll study Reinforced Concrete Design, Engineering Project Management, Machine Learning Fundamentals, and Big Data Applications, preparing you for intelligent infrastructure systems.

Year 5

In your final year, you complete a major engineering honours project and advanced data science coursework. You’ll undertake a Civil Engineering Research Project and a Master’s Level Data Science Capstone, integrating engineering design with predictive modelling and advanced analytics.

Focus Areas (in a string):

Civil infrastructure design, data science, machine learning, structural engineering, predictive analytics, geotechnical engineering, smart infrastructure systems, transportation engineering

Learning Outcomes (in a string):

Design and manage civil infrastructure systems, apply data science and machine learning techniques, analyse complex engineering datasets, develop predictive models for infrastructure, and solve interdisciplinary engineering problems

Professional Alignment (Accreditation):

Accredited by Engineers Australia for the civil engineering component, ensuring strong professional recognition and international engineering standards compliance.

Reputation (Employability Rankings):

Queensland University of Technology is recognised globally for its strong industry engagement and practical learning approach, with graduate employability reflected in rankings such as QS World University Rankings.

Experiential Learning (Research, Projects, Internships etc.)

At the Bachelor of Engineering (Honours) (Civil Engineering) / Master of Data Science at Queensland University of Technology, learning is highly practical and built around solving real infrastructure problems using modern data-driven approaches. You won’t just study engineering theory or data science concepts separately—you’ll actively combine them through projects, simulations, and applied problem-solving tasks. From early in the course, you’ll work with real datasets, engineering models, and digital tools that reflect how modern infrastructure systems are designed, monitored, and improved.

The program strongly emphasises hands-on experience in both engineering design and advanced analytics, helping you develop skills that industry is actively looking for:

Engineering & Data Science Integrated Learning Spaces : Work in collaborative studios where civil engineering design is combined with data modelling, statistics, and machine learning applications for real infrastructure problems
Industry-Standard Software & Analytical Tools : Gain experience with CAD design tools, MATLAB, Python programming, statistical software, and machine learning platforms used in engineering and data science industries
Interdisciplinary Project Work & Capstone Tasks : Complete team-based projects such as predictive infrastructure modelling, smart transport systems, and data-driven environmental analysis
Work-Integrated Learning & Industry Exposure : Access internships and applied learning opportunities through Queensland University of Technology, working with engineering firms, government agencies, and data-focused organisations
Advanced Labs, Computing Facilities & Research Resources : Use engineering laboratories, data science computing labs, and innovation spaces, along with access to the QUT Library for research papers, technical datasets, and academic support

Progression & Future Opportunities

Graduates of the Bachelor of Engineering (Honours) (Civil Engineering) / Master of Data Science at Queensland University of Technology are uniquely positioned for careers at the intersection of engineering, data, and emerging technologies. This combination is especially valuable as industries increasingly rely on data-driven decision-making to design smarter, safer, and more efficient infrastructure.

You could work as a civil engineer, data engineer, infrastructure analyst, machine learning engineer (in infrastructure systems), or smart city data specialist, contributing to the future of digital and sustainable infrastructure:

Career Development & Employability Support: Queensland University of Technology provides personalised career coaching, resume and interview preparation, employer networking events, and access to industry mentors to help students transition into professional roles
Employment Outcomes & Salary Range: Graduates with combined engineering and data science skills are in high demand in Australia, with starting salaries typically ranging from AUD $70,000–$100,000+, especially in data and infrastructure analytics roles
Industry Partnerships & Real-World Exposure: The program is linked with engineering firms, government infrastructure agencies, and technology companies, offering internships, industry projects, and hands-on experience with real datasets and infrastructure systems
Professional Accreditation Value: The civil engineering component is accredited by Engineers Australia, ensuring strong international recognition and long-term professional engineering credibility
Graduate Outcomes: Students graduate with a powerful mix of engineering design skills and advanced data science capability, enabling them to solve complex infrastructure problems using predictive modelling and intelligent systems

Further Academic Progression:
After completing this double degree, students can continue into postgraduate study such as a Master of Engineering, Master of Data Science (advanced research pathways), Master of Artificial Intelligence, or PhD-level research, leading to careers in advanced engineering innovation, data science leadership, or academic research.