LET'S TALK SCIENCE!
Broadening Participation in Artificial Intelligence
National AI Campus is designed to provide foundational skills training in artificial intelligence and machine learning. The program was founded in 2018 at Arkansas State University and has grown since then to a network of more than 45 educational institutions, medical research facilities, and companies across the country. For more information, visit aicamp.us.
The first AI Campus cohort I joined was in 2020, and I've participated continuously since then. It's an integral part of both my educational and professional journeys, and I'm thrilled to be able to share it with learners everywhere.
During the spring semester of 2023, I worked with a team of coaches and mentors across the country to host a cohort of students who joined small groups and learned skills to apply to a variety of projects. In addition to the team meetings and work on each team project, we provided a series of lab assignments to teach basic programming and machine learning concepts.
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Below I've posted information for each of the labs used this semester, including Python notebooks that can be used in Google Colab or your preferred environment. Each lab has 3 notebooks. Level 1 is designed for beginners, with only some code missing for you to complete based on examples provided. Level 2 is designed for intermediate coders, with instructions but most of the code missing. Finally, there's a guide for each one that includes all the code needed to complete the lab. One of the labs uses a .csv file dataset that is provided, the others use datasets included in specific packages.
Ready to learn?
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Binary Classification
In this lab, you'll learn about binary classification - the process of predicting a categorical label when there are only two categories - using a dataset of real and forged banknotes. You'll also learn how regression can be used for binary classification, and how to evaluate the performance, or accuracy, of a classification model.
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Multi-class Classification
Multi-class classification is a technique to assign all samples in a dataset to one of two or more classes.
In this lab, we will implement and compare various classification techniques to a dataset from a pancreatic cancer study to explore the relationship of several diagnostic measurements and patient health.
Each lab should take approximately 30 minutes to complete, and probably more for beginners.
Take your time, and feel free to revisit this page and pause the videos whenever you need to.
Walkthrough: Linear Regression
Guess what? Most programmers spend lots of time looking up function names, syntax, parameters, and error messages. This first video is designed to encourage anyone who wants to learn to code. You'll spend just as much time on Stack Overflow as you will writing code, if not more. That's normal! It's often joked about in the data science and computing community, but not widely discussed in academic settings.
Multi-class Classification:
Uploading a File to Google Colab
This is a short video to demonstrate how to upload the dataset that is used in the Multi-class Classification lab to Google Colab.
More coming soon....work in progress!