Data Science
Data Science Blog
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Exploring the Power of AI in Real Estate Investment: A Personal Experiment
Hello, I hold a PhD in Real Estate, lead MTSU’s Real Estate Studies program in our Economics and Finance Department, and am a faculty affiliate in MTSU’s Data Science Institute. Today, I want to share with you an intriguing experiment I conducted recently, where I harnessed the capabilities of AI to analyze a real-life real…
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Course Policies for Using AI
One of the difficult issues instructors are facing this fall in higher education is to determine what policies are used for AI in the classrooms. The use of generative-AI can effectively break some of the ways instructors might evaluate students. Based on these guidelines and with the help of ChatGPT 4.0, Dr. John Wallin put together…
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AI-assisted Coding: Exploring GitHub Copilot, GitHub Copilot Labs, and the OpenAI API
Since our introduction to GPT in January, there has been an influx of new AI-based coding tools in the market. These tools have been developed not only by large corporations but also by individual users who are leveraging AI engines in their applications. In this talk, we will discuss recent advancements in codes and APIs…
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CDS Seminar: “Environmental Data Science: Recent projects from the Data Science Institute”
The field of environmental science has lagged behind other disciplines in the adaptation of data engineering and data science tools. In this presentation, multiple projects, either currently being developed or recently completed in the Data Science Institute at MTSU will be described.
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CDS Seminar “The Broader Implications of AI in Basic and Applied Sciences: Featuring ChatGPT, GitHub Copilot, and DALL-E 2*”
This panel, of MTSU Faculty members, discussion will bring together experts from a variety of fields to explore the potential benefits and challenges of AI in the basic and applied sciences.
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A quick note on predictive modeling process
Predictive modeling is a vast area; much care needs to be taken to have an effective ready-to-go model.
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Getting a job after graduation
Congratulations you’ve graduated, now let’s get that job.
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Computational Papyrology: Using Data Science to Understand Ancient ManuscriptsÂ
In the 1920s, archeologists from Oxford University discovered over 600 crates of documents buried outside the Egyptian city of Oxyrhynchus.  Since they were found, less than 10% of these manuscripts have been analyzed and published.
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Internship experience becomes an opportunity after graduation for one student
A Data Science student tells of his internship experience and the opportunities that resulted from that summer.
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What should every data scientist know when working with ZIP Codes?
When working with Zip codes, data scientists must fully understand what zip codes are. It’s more complex than just being part of an address.
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