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IS490

Google Analytics Work-Study Elective

2 CreditsBoth

Description

The Google Analytics Work-Study Elective is a six-month internship attachment program under the SMU-Google Squared Data & Analytics Programme. During the attachment period, students work five days a week at an assigned Google Partner company. While undertaking the work-study elective, students may also enroll in 1-2 CUs of courses at SMU during the same term and are allowed to be back in campus up to one day each week. Students will be assigned to a SMU Faculty Advisor and an Internship Supervisor (from the Google Partner company). This elective provides students with an opportunity to do an extended internship with a Google Partner company and applies the digital analytics skillsets that they learnt to contribute to the data and analytics sector in Singapore.

Requisites

Prerequisites: ANLY104 & IS451 - Pre-req

Co-requisites: None

Anti-requisites: None

Attributes

Department: SCIS

Course Level: Undergraduate

Tracks: IS/T4BS: Business Analytics Track

Areas: Advanced Business Technology Major Analytics Major Business Options Econ Major Rel/Econ Options IS Depth Electives Social Sciences/PLE Major-related Technology & Entrepreneurship

Learning Outcomes

1) Explain the key business areas and how digital analytics has impact the business of the internship company 2) Acquire domain-related and industry-relevant knowledge 3) Analyse industry specific problems with understanding of industry constraints and context 4) Identify business objectives, KPIs and performance targets/goals of the required analytics tasks 5) Analyse various tracking methods or implementation, including campaign and conversion tracking 6) Propose practical solutions to task assigned 7) Work with others towards accomplishment of common goals 8) Present the result of an analysis (or a case study of selected aspects of work done) and/or implemented solution 9) Write the work-study elective report to document the tasks completed during the internship, reflection of the work-study process, lessons learned and possible areas of improvement

Graduate Learning Outcomes

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

Competencies

Data Analytics, Business Requirements Mapping, Data Engineering, Data Visualisation, Market Research

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