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Microsoft VS Code IPE Documentation

This Project was carried out by Third Year Students at Imperial College London. Issued by Microsoft, the project was undertaken with the objective to create an 'Interactive Programming Experience' that combines 'The rich editor experience in Visual Studio Code with the interactive programming model of Jupyter Notebooks'.

Getting Started Quick Links:

Introduction
The rise of the data science industry over the past decade can be attributed to the fast adoption of IoT products and social media sites, resulting in monumental amounts of data. Machine Learning can then be used to find patterns or develop algorithms with this data to improve services, tailor advertising and consumer content along with many other applications.  

Background
There are an estimated 3 million data scientists in the world today[1] and the demand for these professionals is expected to grow by 39% before 2020[2]. As a result, more sophisticated and powerful development tools are required for data scientists to carry out their work.

Client & End-User
Microsoft identifies as a ‘developer tools company‘. It currently has a 13% market share in the global cloud computing industry[3] and is the fastest growing company in that sector.

Their recent commitment in being ‘all-in’ on open-source software has propelled their presence in developer and professional networks, meaning that they can reach a vast number of end-users, especially data scientists. 

Competiton
The vast majority of data scientists use Python and R. Jupyter Notebook is currently the prime development choice among data scientists and provides a unique way to view and interact with code written in these languages.

Visual Studio Code is an intelligent lightweight editor that provides a rich development experience. There are many alternatives such as PyCharm and RStudio, however all of these fall short of providing a complete notebook-style coding solution.​

Unique Selling Point
Microsoft proposed this project to combine the powerful editor experience of Visual Studio Code with the interactivity of Jupyter Notebook.

The final product is an open-source extension called neuron, which provides an interactive notebook experience seamlessly integrated with a full code editor.

The goal is to deliver a fresh new experience in a polished environment, addressing a clear gap in the data science developing community.