bus5pr1 analytics project 1

ANALYTICS PROJECT 1

BUS5PR1

2020

Credit points: 15

Subject outline

This subject expatiates knowledge and skills acquired in the course hitherto, by focusing on a real-world, hands-on, industry-focused project that requires students to apply, experiment, create and evaluate an end-to-end analytics solution that addresses complex end-user requirements for data-driven decision-making. Students will learn an agile scrum-based approach that use Jupyter Notebooks, Google Collaboratory, and Python libraries for developing analytics techniques based on machine learning, deep learning and natural language processing algorithms. Professional and interpersonal communication skills required to present an analytics start-up pitch, data-driven insights, analytics teamwork practice and project management updates to an industry based audience will be discussed, demonstrated and assessed. Ethics of artificial intelligence and analytics, data and ICT governance, security management, and related human factors which are equally important to a successful analytics project with positive social impact will be formulated and evaluated in this subject.

SchoolLa Trobe Business School

Credit points15

Subject Co-ordinatorDaswin De Silva

Available to Study Abroad/Exchange StudentsNo

Subject year levelYear Level 5 - Masters

Available as ElectiveNo

Learning ActivitiesN/A

Capstone subjectYes

Subject particulars

Subject rules

PrerequisitesBUS5AP AND BUS5VA AND BUS5PA

Co-requisitesBUS5CA

Incompatible subjectsN/A

Equivalent subjectsN/A

Quota Management StrategyMerit based quota management

Quota-conditions or rulesBy order of application to the Subject Coordinator.

Special conditionsN/A

Minimum credit point requirementN/A

Assumed knowledgeN/A

Career Ready

Career-focusedNo

Work-based learningNo

Self sourced or Uni sourcedN/A

Entire subject or partial subjectN/A

Total hours/days requiredN/A

Location of WBL activity (region)N/A

WBL addtional requirementsN/A

Graduate capabilities & intended learning outcomes

Graduate Capabilities

COMMUNICATION - Communicating and Influencing
DISCIPLINE KNOWLEDGE AND SKILLS
INQUIRY AND ANALYSIS - Creativity and Innovation
INQUIRY AND ANALYSIS - Critical Thinking and Problem Solving
INQUIRY AND ANALYSIS - Research and Evidence-Based Inquiry
PERSONAL AND PROFESSIONAL - Ethical and Social Responsibility

Intended Learning Outcomes

01. Compose, prepare, communicate as well as interpret a comprehensive analytics proposal for complex problems in industrial settings.
02. Identify, compare, develop and apply analytics techniques based on artificial intelligence, machine learning, deep learning and natural language processing algorithms using state-of-the-art technology platforms for agile solution formulations and comparison
03. Demonstrate a practical knowledge of ethics in artificial intelligence and data analytics, data and ICT governance, security management, and related human factors.
04. Develop an ethical and professional mindset towards engagement, interaction and teamwork with industry-focused stakeholders, teaching staff, fellow student as well as datasets, algorithms and insights.

Subject options

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Start date between: and    Key dates

City Campus, 2020, Semester 1, Night

Overview

Online enrolmentYes

Maximum enrolment size120

Subject Instance Co-ordinatorDaswin De Silva

Class requirements

Lecture/WorkshopWeek: 10 - 22
One 3.00 hours lecture/workshop per week on weekdays at night from week 10 to week 22 and delivered via face-to-face.

Assessments

Assessment elementCommentsCategoryContributionHurdle%ILO*

Presentation of analytics project proposal1500 words equivalency task

N/AN/AN/ANo30SILO1

Critical evaluation of findings and insights2500 words equivalency task

N/AN/AN/ANo40SILO1, SILO2, SILO4

Final presentation and report of analytics project at analytics project competition1500 words equivalency task

N/AN/AN/ANo30SILO2, SILO3, SILO4

City Campus, 2020, Semester 2, Night

Overview

Online enrolmentYes

Maximum enrolment size120

Subject Instance Co-ordinatorDaswin De Silva

Class requirements

Lecture/WorkshopWeek: 31 - 43
One 3.00 hours lecture/workshop per week on weekdays at night from week 31 to week 43 and delivered via face-to-face.

Assessments

Assessment elementCommentsCategoryContributionHurdle%ILO*

Presentation of analytics project proposal1500 words equivalency task

N/AN/AN/ANo30SILO1

Critical evaluation of findings and insights2500 words equivalency task

N/AN/AN/ANo40SILO1, SILO2, SILO4

Final presentation and report of analytics project at analytics project competition1500 words equivalency task

N/AN/AN/ANo30SILO2, SILO3, SILO4