Artificial Intelligence sounds scary in itself, but when you add on the online portion it sounds far too intimidating. While I was hesitant to take this class once it was moved to online, I decided to continue with it because it was something I had been looking forward to learning all year. The first day of class my professor announced that he knew this would be a lot of learning and adjusting as we go, everyone would be adjusting to online learning and Richard was willing to be flexible with us. In normal block plan fashion we dove into topics of AI on day 1.
Our first task being to define, What is Artificial Intelligence? As we bounced around ideas we landed on AI being a classification problem, where one is taking labeled data and learning from examples. AI is a statistical analysis of data. For this class, we are focusing on machine learning, which goes hand in hand with AI. This class seems to be working with a lot of different topics including algorithms, linear algebra, and data science. The first week we worked a lot with implementing well known machine learning algorithms such as Nearest Neighbor Model. This algorithm allows us to plot different points on a graph based on our labeled data and ask the computer to find the nearest neighbor to a specific point. As you may be able to assume, this takes a lot of both math and computer science so a good portion of our lectures were simply making sure we were comprehending what mathematics we were going to have to implement. We work really hard in this class to understand the “why” and “how” of our problem before trying to start coding.
While I will be the first to admit I am not a fan of distance learning I am a fan of having recorded lectures. I have found myself motivated (or confused?) enough to go through and watch my lectures again, to pause and take more detailed notes, and to keep track of things that I may have more questions about.
