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BUS5AP Analytics In Practice

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We assume not everyone is familiar with the environment or that they haven’t got an account to  operate on Kaggle. Therefore, the first step is to set ourselves up on Kaggle.
1. Go to Kaggle.com and create an account. There are various ways to create an account but for  the purpose of this subject, please create an account that shows your name (or student ID) clearly.
a. Thinking longer term, make sure this is a professional sign in. If not, create a new email address, etc. as the environment is a reflection of you professionally.

2. Kaggle has evolved to become a self-hosted environment. It runs both R and Python with many pre-built packages installed. This cloud-hosted environment is call a “Kernel” in Kaggle speak. 
a. To explore the Kernel environment, click “Kernels” on the top after signing in.
b. Click “New Kernel” in the centre of the screen and you will be asked to select the data set that you want to work on.
c. Depending on the data set, you will be given a number of programming language options. 
d. Have a play with the environment for now with different data sets and based on what you have learned with R or SQL for example.

3. Kaggle also hosts a number of good tutorials, which you can access here https://www.kaggle.com/wiki/Tutorials
4. As a community site, you need to be aware of what is public and what is hidden. Kernels, data sets, competitions, etc., can be either public or private to invited individuals. Have a look around and make sure you understand your privacy settings.
5. Kaggle has an option call “Kaggle in class” which is used primarily for teaching and learning purposes. This will be the environment used for subsequent exercises, which gives us a more controlled environment for a classroom environment and for assignments.
a. If you like to explore this more, you can do so by going to https://inclass.kaggle.com.
b. There are a few smaller and good starting point data sets already pre-loaded for you to explore.
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