Bachelor of Engineering (Honours) / Bachelor of Data Science

at Griffith University

Modules:
    

• Engineering Mathematics 1
• Engineering Science
• Engineering Materials
• Creative Engineering
• Engineering Mathematics 2
• Engineering Design Practice

Prerequisites: Any General or Applied English subject (Units 3&4, C)
 

English language requirements apply to International applicants and other applicants whose previous study was undertaken in a language other than English. The minimum English language requirements for such applicants for entry to this program are as follows:
 

• A minimum overall band score of 6.5 on IELTS (Academic) with no sub-score of less than 6.0
• OR a minimum score of 575 on TOEFL
• OR an internet-based (iBT) TOEFL score of 79 (no sub-score less than 19)
• OR no score less than 3+ in each skill of the ISLPR (conducted by ISLPR Language Services only)
• OR a minimum overall score of 176 (no score less than 169) on C1 Advanced (formerly Cambridge Certificate in Advanced English) or C2 Proficiency (formerly Cambridge Certificate of Proficiency in English)
• OR an overall score of 58 in the Pearson Test of English (Academic) with no score less than 50.
   

English test results must be no more than two years old.

Indicative annual tuition fee  - AUD $38,500

The indicative annual tuition fee is calculated based on a standard full-time study load which is usually 80 credit points (two full-time trimesters).

Civil engineers provide a major contribution to society by supporting the design and development of essential services, and by managing and improving the built environment. Demand for civil engineering professionals has grown and is expected to continue be an area of high demand. You could find employment in jobs such as chief civil engineer, construction engineer, municipal engineer, structural engineer, transport engineer, water supply distribution engineer, project manager and consulting engineer.

Never have we collected so much data about absolutely everything. From things that happen naturally, like climate change or the birth of galaxies, to all the social businesses, individual movements, corporate decisions and human activities. The data is there for its exploitation by machine learning technology, big data, data mining and other artificial intelligence technologies that coupled with traditional statistical analysis enable to produce insights into the future. Nothing is more valuable than anticipation. Thus, data scientist are finding jobs in multiple disciplines.