Watch Anna talk about her class experience.
Master of Science in Analytics students at UChicago spend most of their classes applying data science to challenges and questions in specific industries like healthcare and finance. Instructor Yuri Balasanov asks students to solve a different data science question in the class Advanced Machine Learning and Artificial Intelligence. The classes’ final project challenges students to write a decision-making function that will compete for a high score in a game of Pac-Man®. Anna Bladey won the top spot when she took the class by embracing this machine-learning challenge.
“The instructions were that we would be given a framework for our decision-making function and then that decision-making function would play the game for us,” said Anna Bladey, winner of the MScA Pac-Man® competition. “The program collects the information about the Pac-Man® environment, puts it into the function, and then outputs the optimal action under those conditions. The program just executes that action each step of the way.”
Using Python and various modern cloud computing environments, Advanced Machine Learning and Artificial Intelligence revolves around real-world projects as a way to teach students to think about present-day problems and analyze big data in new ecosystems. By discussing different approaches to developing insights while deeply exploring the advantages and disadvantages of each one, the class’ goal is to bridge a gap that instructor Dr. Yuri Balasanov sees in typical data science courses taking up these new ways of analyzing big data.
“Teaching these new concepts and methods in class by using textbooks and laptops doesn’t convey the flavor of what working with big data in the world is like today,” says Yuri. “By making the class project-based we are able to combine the depth of discussion that goes into tackling these problems with the high-end technology being used in today’s workplace.”
Anna says she would recommend the class to students who are interested in artificial intelligence and eager to learn more about what is going on at the cutting edge of the data science industry right now. She notes that one of the aspects of the class that makes it advanced is that it’s very much self-directed and that getting an opportunity to apply these new skills and techniques hands-on is particularly helpful.
“Lectures cover what goes on in the world of data science and we’re given some examples of code,” she says. “But the projects are big. They’re hard. You have to work on them for several weeks. And the solutions are not easily found in a textbook. This is all really new stuff."
While challenges associated with data analysis have grown significantly since the era of big data began—from developing the infrastructure for holding data to modifying methods of analysis for working in distributed computational environments—the biggest challenge of all has involved learning to think differently in order to ask questions that could never have arisen when both data streams and technological infrastructure were less complex.
That’s why Advanced Machine Learning and Artificial Intelligence is less focused on problem sets with well-formulated questions and answers than on developing the tools and approaches to problems that will give students the ability to start thinking and asking new questions on their own.
“It’s one of the most challenging classes that the program offers,” Anna says. “I really enjoyed it. It covered a lot of the brand new, cutting-edge topics in data science and artificial intelligence today. And I was given the opportunity to work on things that I'd only ever read about before.”