Back to Modules
SMT483

SMT Project Experience (Applications)

1 CreditsBoth

Description

This course will enable Year 3 or 4 SMT students to apply what they have learnt at SIS to (i) design and implement an application as a team comprising 4 to 6 students (Application); (ii) conduct academic research individually (Research) or (iii) conduct evidence-based analysis of smart city blueprints or data-driven analysis as a team comprising 2 to 3 students (Analysis) to address a real-world urbanization or societal challenge towards realizing smart cities. Students who have confirmed their enrolment with the Course Coordinator should bid for SMT483 section(s) of the respective supervisor (where applicable) during BOSS 2A and onwards. e$10 bid amount will suffice. If students do not secure their bid by BOSS 2A Win 3, they can request to be enrolled offline and e$20 will be deducted.

Requisites

Prerequisites: IS112/IS105 & IS110/SMT110 & POSC101 & SMT203 - Pre-req

Co-requisites: None

Anti-requisites: None

Attributes

Department: SCIS

Course Level: Undergraduate

Tracks: N/A

Areas: Business Options Econ Major Rel/Econ Options Smart-City Mgmt &Tech Core (Intake 2018 & earlier) Social Sciences/PLE Major-related

Learning Outcomes

Application Showcase expertise in executing a project Experience developing some technology deliverables Experience working in a team environment with a sponsored project Learn about an industry or technology not otherwise covered in the curriculum Work on that will be used by the sponsora complex and real project and deliver a solution Document findings in a report to demonstrate value to sponsor Research have participated in an academic research project have acquired special communication and presentation skills have acquired an appreciation for the intellectual process of inquiry and creative thinking have acquired background knowledge and experience in the process of research have surveyed and analysed relevant literature in the research area have acquired academic writing skills Analysis have experience with preprocessing of various types of data have applied fundamentals of data and decision analytics on real world data have developed a data-driven approach to solve real-world problems document findings in a report to demonstrate value to sponsor

Graduate Learning Outcomes

Disciplinary Knowledge, Multidisciplinary Knowledge, Interdisciplinary Knowledge, Critical thinking & problem solving, Innovation and enterprising skills, Collaboration and leadership, Intercultural understanding and sensitivity, Understanding of sustainability issues, Self-directed learning, Resilience

Competencies

Strategy Planning, Research, Business Performance Management, Infrastructure Support, Service Level Management

View Source Listing