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FloCon Data Science Concepts and Techniques

Andrew Fast, Ph.D.

This repository contains the support files for "Introduction to Data Science - Concepts and Techniques" course being presented in conjunction with FloCon. These files provide some minimal examples of traditional data science algorithms applied to NetFlow and other cybersecurity data.

There multiple ways to run and access this data:

Run In A Browser

The course is available in a browser via the Binder Service. Click the badge below to get started.

Binder

Run with Anaconda

Anaconda is a popular Python distribution. It includes the ability to run Jupyter Notebooks. Download Anaconda here.

You will need to either:

Once the files are downloaded, you will need to install the required packages. Choose ONE of the following methods:

  • Install the packages using conda or pip on the CLI e.g., conda install --file requirements.txt
  • Evaluate dependencies.ipynb via Jupyter Notebooks.

Run using Docker

Docker is a popular method for running software in "containers". First, you will need to grab the files from GitHub using ONE of the following methods:

Then navigate on the command-line to the directory with the files then from the terminal prompt type: docker run -p 8888:8888 -v $(pwd):/home/jovyan/work jupyter/minimal-notebook Then copy and paste the link that appears in the terminal window into your browser

You will need to install the proper Python dependencies for the course. This can be achieved via ONE of the following methods:

  • Evaluate dependencies.ipynb via Jupyter Notebooks.
  • Open a terminal from the "New" drop down menu in the top right of your screen, then type cd work; pip install -r requirements.txt at the prompt

Run using VSCode

VSCode is a common tool for software engineers. You will need to install a plugin for VSCode titled "Jupyter Notebook" from the VSCode Marketplace. You will also need to ensure the ipykernel python module is installed and available in your environment. Then download the notebook files for the course:

Finally, install the dependencies using ONE of the following methods:

  • Evaluate dependencies.ipynb via Jupyter Notebooks.
  • Open a new terminal window then type pip install -r requirements.txt at the prompt