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Data Science Postgraduate Project

COSC2667
Closed
RMIT University
RMIT University
Melbourne, Victoria, Australia
Christopher James
Christopher James
Engagement Senior Coordinator
(12)
4
Timeline
  • July 18, 2021
    Experience start
  • October 19, 2021
    Experience end
Experience
1/10 project matches
Dates set by experience
Preferred companies
Anywhere
Any
Any industries
Categories
Data analysis
Skills
competitive analysis business analytics marketing strategy data analysis
Learner goals and capabilities

Students will dedicate 240 hours over a 12 week period to complete a data science based project. We ask that the client e-meets candidates for 1 hour a week to keep them on track.

This is a project-based course where students learn through meetings and informal discussions with other students, the project manager and client. Their learning is in the ’doing’, where students will carry out all the necessary steps to successfully complete the project.

All learning activities in this course are based on applying data science knowledge in a process of planning and executing a substantial research-based project or industry-sponsored capstone project experience.

Learners
Post-graduate
Any level
4 learners
Project
240 hours per learner
Learners self-assign
Teams of 4
Expected outcomes and deliverables

Please see examples of previous projects above as an indication of what can be achieved. Project outcomes can be discussed once a project has been proposed.

Project timeline
  • July 18, 2021
    Experience start
  • October 19, 2021
    Experience end
Project Examples

Examples of previous projects:

• Identify and profile customers of a retailer to better target their offering.

• Prototype approach to identifying culture in businesses using natural language processing.

• Establishing correlations and relationships between variables to improve mailouts.

• Predicting and estimating part attributes that are useful for determining.

• Analysing survey data to identify sentiment towards identified topics and product/brand.

• Predicting and identifying students at risk of failure for early intervention.

• Building of dashboards to summarise and analyse company’s performance.

• Cleaning and merging of multiple data sets to perform subsequent summarisation and analysis.

Linked templates
Potential Customer Segmentation Analysis View all
Companies must answer the following questions to submit a match request to this experience:

Have a contact for students to liaise with during the project.

Be available for a quick phone call with the instructor to initiate your relationship and confirm your scope is an appropriate fit for the course. 1 hour a week to meet students and keep them on track.