Setting Up and Provision a Windows Instance at AWS

This series of six videos shows how to create a windows instance at Amazon Web services and provision it with Anaconda Python and the R statistics software. The video also shows how to install the antivirus software ClamWin and ClamSentinel and the Linux-like utilities CYGWIN. The objective is to create a platform for data science.

Note: Amazon Web Services makes changes to its web pages and other aspects of its products frequently. As a result, these videos may deviate somewhat from what you find at AWS. This problem is inevitable when making tutorials (as I am) about web sites and services you do not own. You should be able to figure things out, but if there are significant changes, please feel free to alert me by commenting or messaging me either on YouTube or here. I expect to check and update these videos about once per year.

Introduction (2 minutes)


Step 1: Setting Up an Amazon Web Services Account (11 minutes)

(Requires a credit card and access to a phone.)



Step 2: Launching a Windows Instance (20 minutes)



Step 3: Connecting to the Windows Instance (17 minutes)



Step 4: Provisioning the Windows Instance with Open Source Software for Data Science (30 minutes)



Wrapping Up: Checking the Installations (15 minutes)


8 thoughts on “Setting Up and Provision a Windows Instance at AWS

  1. These are a wonderful collection of videos introducing Python to new users. Professor Easton presents the material in a clear and easy to understand manner. I’ve taken a number of online video classes and Professor Easton’s Python series ranks up with the very best.

    • Glenn, thank you very much for your extremely kind comment. I really appreciate your taking the time.

      I have two more videos to make to complete the introductory series (one on basic file handling and the other on the import statement and modules) and then I plan to start on some intermediate topics (like list comprehensions, error handling, etc.).

      Thank you again.

  2. I agree with Glenn, these Python videos are the best. The explanation and examples of objects were especially helpful for me. I appreciate Professor Easton’s work making the videos available to everyone. I am looking forward to continuing the series.


  3. Another voice in a growing chorus it seems… Thanks for these clear and concise tutorials. I’ve both benefited and enjoyed the.

    I’ve programmed in other languages, so programming concepts are not new to me, but I thought your approach – discussing data and objects first, then introducing control structures at the end was interesting. It seems that in the case of Python, this is a better approach than in other languages.

    Thank-you again, Prof. Easton

    • Thank you for your kind comments and I am glad that the Python with Spyder series was useful to you.

      I also appreciate your noticing and commenting on the fact that the series is heavily oriented towards data structures. There are two reasons for this, both related to the fact that I developed the series as a part of a data science elective class for tech-oriented MBA students. First, I wanted them to be able to use Python to interface with APIs on the web (such as Twitter’s) in order to get data. It turns out that understanding and using these APIs requires much more understanding of data structures than it does flow control as the flow control is often hidden inside of the methods associated with the key data structures. The other reason is that I think that in order to be minimally conversant with software people you have to have some idea of what object oriented programming is about and why concepts such as objects, inheritance, and encapsulation are important. I also wanted to make sure that my students knew what an IDE is (thus, Spyder and the reason that I present the language in the context of the IDE).

      In my data science course, we use Python in two major ways: (1) to access APIs to get data (as I already said above), and (2) to pre-process very large data sets before analyzing them using R. This also explains the things that are left out of the series. For example, I do not discuss user interfaces of any kind (like GUIs) or any sort of event-based programming.

      Because of what I was trying to do with the data science class and because of the nature of my target audience I did not find any other tutorial that did quite what I wanted. There are many excellent tutorials out there, but I did not find any that quite hit the mark for my class. This is why I made the effort to make the videos. Give the amount of interest these video seems to have generated, the niche I was aiming at appears to extend far beyond just my students.

      Thank you again for taking the time to comment.


      George Easton

  4. Professor Easton,

    Your courses continue to help me immensely as I try to learn Python from a zero programming background. Thank you for posting these videos. You are thorough and move at just the right pace; I wish I had professors like you in college. Know that people ARE watching these and you have made a huge difference in my Python journey. Thanks again!


Leave a Comment

Time limit is exhausted. Please reload CAPTCHA.