Assignment Task
Brief
The Bureau of Infrastructure, Transport and Regional Economics (BITRE) publishes monthly air travel statistics between various cities. Your task is to build a model for predicting the passenger traffic between Melbourne and Sydney using this data. This model should predict the volume of revenue passengers for each month in 2019.
When building this model, please keep in mind the following:
We are only concerned with the revenue passenger traffic.
We are only concerned with traffic from Melbourne (MEL) to Sydney (SYD).
Air traffic can be highly seasonal in nature and comparisons are often made in comparison with a similar period in the previous year.
Your solution should:
Load the source data.
Build a model that is appropriate for these data.
Use the model to forecast the revenue passengers between Melbourne (MEL) and Sydney (SYD) for each month in 2019 and print this forecast to the console (stdout).
Your Solution
We prefer your solution to be written in Python but you may use another programming language/environment if you wish. You are free to use any libraries as you see fit. Solutions in Excel (or other spreadsheet tools) will not be accepted. You are encouraged to run and test your solution before submitting it; to do so, you can obtain a Python environment by installing WinPython, use an online environment such as repl.it/languages/python or use any other Python environment of your choosing.
You may spend as much time as you need on this exercise, but we would prefer you to not spend more than 1-2 hours.
The deliverable for this exercise is a single source file (.py, .ipynb or equivalent for other languages) or a Zip file if your solution has multiple source files.
We will be assessing your solution by:
Your ability to interpret and manipulate data;
Your ability to apply a principled and mathematically rigorous approach to solving a data science problem; and
Your ability to write clear, concise and readable code.
When working on your solution, please keep in mind that:
We are not looking for one “perfect” solution. Rather, we are looking for you to demonstrate your ability to choose a reasonable approach amongst the many possible approaches.
We will not be benchmarking your model against a ‘ground truth’.
We are not looking for extensive validation of your results.
In case something is not clear, please feel free to make assumptions. Include this within comments as part of your code.
We’ll ask you to present back your findings and welcome the inclusion of any additional insights drawn.
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