What about AI? - Ranger College Library at Ranger College

Data Analysis and Prediction

On the surface, these may not seem like student tasks, but analyzing statistics and being able to make informed choices based on your findings is exactly what students should be able to do.

Tasks: Extracting insights from data, identifying patterns, and forecasting future trends.
- Predictive Analytics: Forecasting future events (e.g., customer churn, sales forecasting, fraud detection).
- Data Cleaning and Preparation: Automating the process of making data ready for analysis.
- Anomaly Detection: Identifying unusual patterns or outliers in data (e.g., fraudulent transactions).
- Business Intelligence (BI) Augmentation: Enhancing traditional BI with AI-driven insights.
- Risk Modeling: Assessing and quantifying financial or operational risks.

Programs/Platforms:
- Google Cloud AI Platform (Vertex AI, BigQuery ML): Comprehensive suite for building, deploying, and managing ML models, including predictive analytics. These are really big picture programs for creating entirely new AI programs.
- AWS SageMaker: Fully managed service for building, training, and deploying machine learning models.
- Azure Machine Learning: Microsoft's cloud-based platform for ML.
- TensorFlow & PyTorch: Underlying frameworks for building custom predictive models.
- R: Statistical programming language widely used for data analysis and machine learning.
- Databricks: Data platform that integrates AI/ML capabilities for large-scale data analysis.

Recent Posts

Lessening the impact of AI on thinking skills

As most of my regular readers know, I read widely on AI subjects and very often find things I want to share. This week's post comes from David Moldawer’s blog, The Maven Game, and his post, The Power of a Blue Book. Very much of what he said is what I wish I had thought of myself, but like the cheating mentioned in his post, I am letting someone else do my thinking for me here. What we have to recognize is that students are going to use AI, they are going to use it to cheat, and the detectors we use provide so many false positives that they are almost useless. The battle against LLM abuse by students is already lost. So what can we do instead? First, acknowledge the long-known fact that writing is a significant part of learning. Creating a sentence is hard work and creating multiple sentences that go together coherently is really hard. If we let LLMs do the writing, we are doing a disservice to them and us. Second, we have to acknowledge that the only solution is to write. In the classroom, during class time, create assignments that require them to think and put it on paper. This isn’t easy, I know. We already have too much to cover and too little time to do it, but we also sacrifice hard assignments for simpler things that can be easily graded by Canvas. Students need hard assignments to learn and we have to grade them. I thought I was doing this for my History 2321/2 classes at Dallas College. The plan was to spend the first ten minutes of each class having the students write a summary of the readings they were supposed to have done before class. I was a new teacher and let it go a little awry. They would come to class with their book, reading for highlights and copying them down. At first, I let them, thinking that at least they were looking at the book. Soon, though, I had allowed a pattern to be established and I did not know how to break it. Grading wasn’t much work. There was never more than half a page. I could look at it for a few seconds and catch anything wrong. It was pretty much a matter of ticking off the assignments as complete. Now, if I had not allowed books, they would have had to think for themselves, they would have gotten in the habit of doing the reading before class, and the grading would not have been any harder. Yeah, I will do that next time. You could try it....

Consensus now has full text access

Consensus was great when it provided abstract information for relevant journal articles, but they have updated their access, and now you get search results that pull straight from the full text of the papers. In some ways, this will be great. We all know abstracts rarely provide the information you want. With the new full-text access, you won’t have to search through a 120 page article to find the relevant parts. Consensus does that for you. Of course, it is only a program and is working from your prompts, so some tweaking will definitely be required. It is also a good idea to pull the full articles to make sure the AI did not miss anything, but this is another tool that will save you enough time to make it worthwhile....

Data Analysis and Prediction

Data Analysis and PredictionOn the surface, these may not seem like student tasks, but analyzing statistics and being able to make informed choices based on your findings is exactly what students should be able to do.Tasks: Extracting insights from data, identifying patterns, and forecasting future trends.Predictive Analytics: Forecasting future events (e.g., customer churn, sales forecasting, fraud detection).Data Cleaning and Preparation: Automating the process of making data ready for analysis.Anomaly Detection: Identifying unusual patterns or outliers in data (e.g., fraudulent transactions).Business Intelligence (BI) Augmentation: Enhancing traditional BI with AI-driven insights.Risk Modeling: Assessing and quantifying financial or operational risks. Programs/Platforms:Google Cloud AI Platform (Vertex AI, BigQuery ML): Comprehensive suite for building, deploying, and managing ML models, including predictive analytics. These are really big picture programs for creating entirely new AI programs. AWS SageMaker: Fully managed service for building, training, and deploying machine learning models.Azure Machine Learning: Microsoft's cloud-based platform for ML.TensorFlow & PyTorch: Underlying frameworks for building custom predictive models.R: Statistical programming language widely used for data analysis and machine learning.Databricks: Data platform that integrates AI/ML capabilities for large-scale data analysis....

Generative AI

Generative AI (Art, Music, Code, etc.)These are really cool tools and will come in handy for creative assignmentsTasks: Creating new, original content based on learned patterns from existing data.Image Generation: Creating realistic or artistic images from text prompts (text-to-image).Music Composition: Generating original musical pieces.Video Generation: Creating videos from text or images.Code Generation: Writing code snippets or entire programs.Text-to-3D: Generating 3D models from text descriptions.Programs/Platforms:DALL-E 3 (OpenAI): Leading text-to-image generator, integrated with ChatGPT.Midjourney: Highly popular AI art generator known for its artistic and often surreal outputs.Stable Diffusion: Open-source text-to-image model that can be run locally or via cloud services.AIVA (Artificial Intelligence Virtual Artist): AI-powered music composition tool.Suno AI, Boomy, Mubert, Udio: AI platforms for generating royalty-free music and songs.Runway: Creates AI-generated images, animations, and 3D models.ChatGPT/Gemini: While primarily text-based, they can also generate code, creative text formats, and even music ideas....

Data Analysis and Prediction

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