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IS464

Data Analytics and Technology Guided External Course

1 CreditsTerm 2

Description

This course is structured as a guided-by-instructor course with content provided by Google through the Google Career Certificates (hosted on online learning platform, Coursera) together with guidance and assessments by SMU. It incorporates industry or career certification in the undergraduate study to equip students with professional and technical skills. Data Analytics and Technology Guided External Course is part of the SMU-KPMG Analytics and Cloud Technology Work Study Program in partnership with Google. Students need to clear this course and its corresponding Google Career Certificate before embarking on a six-month work-study with KPMG. There are two certificates: 1) Google Data Analytics Professional Certificate aims to give students the skillsets on collecting, transforming, organizing, and visualizing data in order to draw conclusions and drive informed decision making; 2) Google IT Automation with Python Professional Certificate focuses on equipping students to use Python in automating common system administration tasks, troubleshoot, debug complex problems, and apply automation at scale using configuration management and the Cloud. NOTE! This course is only open to students accepted into the SMU-KPMG Analytics and Cloud Technology Work Study Program in partnership with Google and enrollment will be done offline with e$20 deduction.

Requisites

Prerequisites: None

Co-requisites: None

Anti-requisites: None

Attributes

Department: SCIS

Course Level: Undergraduate

Tracks: N/A

Areas: Business Options Digital Business Electives Econ Major Rel/Econ Options Grad Req - Dig Tech/Data Ana (Intake 2024 onwards) IS Depth Electives IT Solution Development Electives Social Sciences/PLE Major-related

Learning Outcomes

1. Acquire industry best practices from Google professional training materials 2. Explore the roles of data or IT automation professionals within an organization 3. Communicate insights to stakeholders through practice and case studies 4. Implement the appropriate strategies and solutions to solve real-world problems (either to build regression and machine learning models to analyze and interpret data, or to automate tasks by writing Python scripts) 5. Prepare and deliver presentation to demonstrate findings from case studies

Graduate Learning Outcomes

Disciplinary Knowledge, Multidisciplinary Knowledge, Interdisciplinary Knowledge, Critical thinking & problem solving, Collaboration and leadership, Communication, Self-directed learning

Competencies

Data Analytics, Business Requirements Mapping, Cloud Computing, Software Configuration, Stakeholder Management