Resources for Current Students
As a MSIA graduate student, you will find a variety ways to engage in furthering your education beyond the classroom. To keep informed about opportunities to get involved check back here regularly.
Student advising takes place in the late fall and late spring. After contacting your advisor to review your course choices and plan of study, you will be given an advising code to register for classes.
The plan of study must list all courses you intend to take for your degree. We require the plan of study to be completed prior to 50% program completion. For full-time students, your plan of study should be completed before the end of your second semester.
The plan of study is not permanent and can be changed up until the submission of your final plan of study. A finalized plan of study is due at the beginning of the semester in which you intend to graduate.
The capstone course is your opportunity to gain real industry experience by working on a project involving data. In short, a capstone project will have:
- A faculty mentor
- A data project/internship
- A paper and presentation
View the PDF for more detailed information:
MSIA Book Club:
Join MSIA students in reading and discussing current literature in data analytics. Discussions are held regularly on Zoom. For more information contact Ian Skarring (firstname.lastname@example.org).
Current book selection:
Building Machine Learning Powered Applications: Going to Idea to Product by Emmanuel Ameisen
Other Learning Resources:
Some helpful tips for beginning to acquire programming skills in R may be found on this introductory website: https://education.rstudio.com/learn/beginner/
Download and install R studio: https://rstudio.com/products/rstudio/
The Comprehensive R Archive Network has a wealth of excellent resources and packages for growing your programming skills in R.
Python’s official website has excellent resources for getting downloading and getting started with programming in Python: https://www.python.org/about/gettingstarted/
Google Colab offers a comprehensive cloud based juypter notebook that functions like a google doc in your google job. Login with your gmail account or UNCG email and get started here: https://colab.research.google.com/notebooks/intro.ipynb
SAS Enterprise Miner, SAS Enterprise Guide, and SAS 9.4 may be accessed through your UNCG mycloud account: https://mycloud.uncg.edu/logon/LogonPoint/tmindex.html
SAS also offers a wide variety free tutorials to UNCG students. Get started by setting up an account using your UNCG email:
Programming, Statistics and Machine Learning Books:
R for Data Science by Garrett Grolemund and Hadley Wickham
Machine Learning with R, 3rd Edition by Brett Lanz
Introduction to Machine Learning with Python by Andreas C. Müller and Sarah Guido
Python Data Science Handbook by Jake VanderPlas
Practical Statistics for Data Scientists, 2nd Edition by Peter Bruce, Andrew Bruce, Peter Gedeck