Work Integrated Learning in Data Analytics
Timeline
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August 2, 2023Experience start
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August 2, 2023Progress presentation
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August 4, 2023Problem Statement
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August 6, 2023Project Scope Meeting
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August 13, 2023Project Plan
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November 9, 2023Final report and final presentation
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November 10, 2023Experience end
Timeline
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August 2, 2023Experience start
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August 2, 2023Progress presentation
A clear presentation of the progress and stage achievements.
-
August 4, 2023Problem Statement
The problem statement should identify the question/problem, and a brief description of the data set(s). This describes what the problem is, who the problem affects, why research is needed, and how your project will contribute to solving it. A problem statement serve as the basis for your project pr
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August 6, 2023Project Scope Meeting
Meeting between students and company to confirm: project scope, communication styles, and important dates.
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August 13, 2023Project Plan
Aims and objectives;literature review and research plan.
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November 9, 2023Final report and final presentation
A final academic report detailing introduction, literature review, methodology, result and discussion. A final presentation shows clearly the problem, how the problem was solved and the clear project deliverables.
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November 10, 2023Experience end
Categories
Customer segmentation Machine learning Data visualization Data analysis Data modellingSkills
programming languages statistical analysis machine learning data analytics data modelingThis work integrated learning course addresses the application of analytics and statistics in a real world situation for final year Master of Analytics, Master of Statistics and Operations Research and Bachelor of Analytics students. The projects include data pre-processing and cleaning, data wrangling and exploration, data visualisation (such as dashboard), time series analysis, multivariate analysis, predictive modelling, quality control, regression, machine learning, , experimental design and optimisation. Computation tools include in particular querying language (SQL), R, Python, SAS, and Matlab.
Our WIL projects have helped big and small companies improving their service and efficiency using current analytics and data science techniques. The WIL also provides a pathway for industry to recruit excellent graduates. Some employers report that our students bring fresh ideas and approaches to the workplace, sharing the latest research and thinking in the field they study.
A well documented final report and final presentation from our students.
Project timeline
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August 2, 2023Experience start
-
August 2, 2023Progress presentation
-
August 4, 2023Problem Statement
-
August 6, 2023Project Scope Meeting
-
August 13, 2023Project Plan
-
November 9, 2023Final report and final presentation
-
November 10, 2023Experience end
Timeline
-
August 2, 2023Experience start
-
August 2, 2023Progress presentation
A clear presentation of the progress and stage achievements.
-
August 4, 2023Problem Statement
The problem statement should identify the question/problem, and a brief description of the data set(s). This describes what the problem is, who the problem affects, why research is needed, and how your project will contribute to solving it. A problem statement serve as the basis for your project pr
-
August 6, 2023Project Scope Meeting
Meeting between students and company to confirm: project scope, communication styles, and important dates.
-
August 13, 2023Project Plan
Aims and objectives;literature review and research plan.
-
November 9, 2023Final report and final presentation
A final academic report detailing introduction, literature review, methodology, result and discussion. A final presentation shows clearly the problem, how the problem was solved and the clear project deliverables.
-
November 10, 2023Experience end
Project Examples
Industry projects can be relatively small in scope and (at a minimum) only require the affiliated organisation to provide a data set, or research problem that has been encountered and would be suitable for the students to solve.
In this course, students apply a wide range of data analytical methods and tools covered in the whole program.
Example 1: Data Visualisation project. A train link company was interested in how the on-time running of the networks can be best visualised, and where the pinch points are in the networks. Our students utilised general data visualisation and geospatial data visualisation tools to help industry partners locating the worst performing services and if some services have to be removed.
Example 2: Water Utility project. One of the largest water supply companies in Melbourne, has a yearly maintenance program for sewer reticulation cleaning including key customers and key events. The company was interested in finding out how effective these programs are, and if the frequency of blockages in these assets has come down as a result of preventative maintenance programs. Our students deciphered whether prevention programs reduce the need for responses by making use of multivariate analysis of variance techniques. Time-to-failure analyses highlighted whether prevention programs can extend the time before a failure is seen.
Example 3: Customer Segmentation for Supermarkets. One of the largest supermarket chains in Australia. Our students have built a customer segmentation model that has been used by sales to segment their fresh produce customers based on behaviour, types of products and amounts of products purchased.
Example 4: High Education Enrolment Forecast for RMIT University.
Example 5: Customer Service Improvement Using Natural Language Processing.
Companies must answer the following questions to submit a match request to this experience:
Do you acknowledge that the outcome of this project will need to be submitted by students to a course coordinator for marking?
Get involved in the assessments of students' progress and final report
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.
Be able to set up regular meetings with students to answer their domain questions
Provide a dedicated contact who is available to answer periodic emails or phone calls over the duration of the project to address students' questions.
Timeline
-
August 2, 2023Experience start
-
August 2, 2023Progress presentation
-
August 4, 2023Problem Statement
-
August 6, 2023Project Scope Meeting
-
August 13, 2023Project Plan
-
November 9, 2023Final report and final presentation
-
November 10, 2023Experience end
Timeline
-
August 2, 2023Experience start
-
August 2, 2023Progress presentation
A clear presentation of the progress and stage achievements.
-
August 4, 2023Problem Statement
The problem statement should identify the question/problem, and a brief description of the data set(s). This describes what the problem is, who the problem affects, why research is needed, and how your project will contribute to solving it. A problem statement serve as the basis for your project pr
-
August 6, 2023Project Scope Meeting
Meeting between students and company to confirm: project scope, communication styles, and important dates.
-
August 13, 2023Project Plan
Aims and objectives;literature review and research plan.
-
November 9, 2023Final report and final presentation
A final academic report detailing introduction, literature review, methodology, result and discussion. A final presentation shows clearly the problem, how the problem was solved and the clear project deliverables.
-
November 10, 2023Experience end