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.

School: La Trobe Business School (Pre 2022)

Credit points: 15

Subject Co-ordinator: Daswin De Silva

Available to Study Abroad/Exchange Students: No

Subject year level: Year Level 5 - Masters

Exchange Students: No

Available as Elective: No

Learning Activities: N/A

Capstone subject: Yes

Subject particulars

Subject rules

Prerequisites: BUS5AP AND BUS5VA AND BUS5PA

Co-requisites: BUS5CA

Incompatible subjects: N/A

Equivalent subjects: N/A

Quota Management Strategy: Merit based quota management

Quota-conditions or rules: By order of application to the Subject Coordinator.

Special conditions: N/A

Minimum credit point requirement: N/A

Assumed knowledge: N/A

Career Ready

Career-focused: No

Work-based learning: No

Self sourced or Uni sourced: N/A

Entire subject or partial subject: N/A

Total hours/days required: N/A

Location of WBL activity (region): N/A

WBL addtional requirements: N/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.

City Campus, 2020, Semester 1, Night

Overview

Online enrolment: Yes

Maximum enrolment size: 120

Enrolment information: N/A

Subject Instance Co-ordinator: Daswin 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 element	Comments	Category	Contribution	Hurdle	%	ILO*
Presentation of analytics project proposal1500 words equivalency task	N/A	N/A	N/A	No	30	SILO1
Critical evaluation of findings and insights2500 words equivalency task	N/A	N/A	N/A	No	40	SILO1, SILO2, SILO4
Final presentation and report of analytics project at analytics project competition1500 words equivalency task	N/A	N/A	N/A	No	30	SILO2, SILO3, SILO4

City Campus, 2020, Semester 2, Night