Tag Archives: tools

Tools For Writing a Data Science Dissertation

It can be a long and difficult task. It takes dedication, a good topic, a helpful advisor, some meetings, and a bit of paperwork. However, it is not impossible, and here are some tools to make it easier (hopefully).

This is not intended to be a guide for selecting a topic. I am not qualified to provide that type of advice, but I will say, choose both a topic and an advisor you find interesting. This is intended to be a collection of tools I found useful during my journey. I do not think the list is specific to data science; it could easily apply to: mathematics, statistics, computer science, engineering, or any other highly quantitative field.

All these tools have free versions to get you started. A few have discounted upgrades for students.

  • Use an online LaTeX tool such as ShareLaTeX.
    How does this tool benefit you? It saves you from having to install a version of LaTeX, stores history of your previous versions of the document, and allows you to write on any machine with an internet connection. In addition, ShareLaTeX has existing templates for many, many Universities. Students can even get half-priced premium accounts to collaborate and sync with Github and Dropbox. While LaTeX is not perfect, I do not know of any better tool for writing mathematical documents.
  • Use GitHub to store you data and source code
    At some point in time, hopefully you will want to share your results. GitHub is the defacto standard for sharing open source code. It also works very well for storing data as well, even large datasets. You might also discover another open source project you want to get involved with. As a definite bonus, many future non-academic employers encourage a GitHub account during the application process. Thus, the sooner you start the better.
  • Use a Cloud Computing Platform such as Sense.
    Don’t spend your time building a cluster of computers unless your dissertation topic involves cluster computing. Solve your own problem, not infrastructure problems. Sense and others provide access to massive computing power for cheap or low cost. Plus, it provides collaboration, sharing, scheduling, notifications, analysis recreation, and many other features you might find beneficial.
  • Use Create.ly for creating diagrams.
    Creating flowcharts and technical diagrams can be a pain. Especially if you do not have expensive diagram software. Creately is a simple solution to this problem.

There is your list of helpful tools for writing a data science dissertation. Do you have any tools you think I missed? If so, please leave a comment.

50 Top Open Source Tools for Big Data – Datamation

50 Top Open Source Tools for Big Data – Datamation.

The list is about 6 months old, but it still covers all the ones I would have listed and quite a few more.

3 Secrets for Aspiring Data Scientists | Software Advice

Michael Koploy wrote 3 Secrets for Aspiring Data Scientists about what it takes to enter a career as a data scientist. He lays out 3 steps:

  1. Sharpen Your Scientific Saw – Hone your math and science skills
  2. Learn the Language of Business – Data Scientists need to explain the data in business terms
  3. Keep Adding to Your Technical Toolbelt – Learn all the tools you can (NoSQL, Excel, Hadoop,…)

The article is a nice read. http://blog.softwareadvice.com/articles/bi/3-career-secrets-for-data-scientists-1101712/