40 Years of STEM Innovation

Course Description: Artificial intelligence is a controversial technology due to its newness in all fields of business. Yet the benefits of AI are undeniable; with thoughtful inputs, AI can generate millions of potential solutions that would take a human being months or years to develop through trial and error. The key is making sure the inputs net the expected results, and to do that effectively, the next generation of the work force must understand the basics of AI systems and how to use logic and ethics to generate the output that is needed for their careers.

Course Description: Artificial intelligence and learning language models are dependent on human inputs (often prompt generation) to create unique and innovative output. The quality of the input has different effects on the output, often very surprising ones. To create excellent products and output, the first step is to learn how to control and capitalize on those surprises through careful and thoughtful prompt generation.

Course Description: The best laid plans often go astray, to paraphrase John Steinbeck. Even with excellent, thoughtful inputs into an AI system, there can still be unforeseen issues with bias in data. Additionally, as society changes and grows, new parameters might need to be added to the data. This course will show you how to manipulate data to resolve bias (as much as possible) or to update existing data to refine the AI output.

Course Description: Data analysis is a multi-step cycle that informs itself. Many STEM students are excellent at the first steps – data generation and collection – but where do we go from there? This course explores all steps in the data cycle, from data generation to data presentation. Even the best data collection practices need strong analysis and most importantly, excellent presentation to make that data useful, valuable, and correctly understood.

Course Description: Data analysis, on a large scale, is not usually done by hand entirely; it relies on tools and programs to aid in this process for accuracy and speed. However, it can be tough to determine which tool is best for the job without a familiarity with the basic functions of the most used tools in data analysis. An overview of the most current data analysis systems will make up the bulk of this course.

Course Description: Where does data come from? Are there rules about how you can collect data online? Web scraping is one way to collect data online, with permission from the websites being scraped. It’s a great way to learn about trends, find unusual facts, and look at data in whole new light. It can also be used to “gamify” tasks and improve your own daily habits.

Course Description: We will speak on the myriad of opportunities available in cybersecurity and the steps students should take to prepare themselves in this burgeoning field of work.

Course Description: A joint session to discuss college financing and the admissions process. Everything you need to know about FAFSA, scholarships, what to expect when you matriculate, and where to find campus resources to help you get the most from your college experience.

Course Description: The metaverse is a rapidly evolving digital environment where people can connect, create, and collaborate in 3D spaces. While still emerging, the metaverse has the potential to transform education, business, and culture by blending virtual and real-world experiences. Understanding the metaverse allows learners to explore its creative possibilities while also considering the ethical, social, and economic implications.

Course Description: Quantum computing is a math-forward field of study that has new breakthroughs every year. What are the possible applications for a quantum computer, and how could quantum technology revolutionize our modern world?

Course Description: We will speak on the myriad of opportunities available in cybersecurity and the steps students should take to prepare themselves in this burgeoning field of work.

Course Description: In quantum computing, there are three major problems that have not been solved: quantum decoherence, error correction, and stability. These problems and the effects they have will be described along with the best solutions we’ve created so far. The person who solves these problems may be in the classroom today, waiting to claim their place in history!