Applied AI in Python

This semester-long course will give students hands-on experience with artificial intelligence (AI) by applying machine learning models and libraries using the Python programming language. The course will explore the construction of algorithms which can learn from and make predictions on real-world data. Students will firstly recap on Python loops, lists and dictionaries and learn how to manage file input and output. They will then learn how to use the Pandas and Numpy libraries to analyze and interpret data. Students will then be introduced to the Tensorflow and Keras frameworks and build machine learning models to analyze images and text. Students will apply their knowledge to implement and refine machine learning models to a data set of their choice and understand the ethical implications. Finally, students will present their findings to an authentic audience. Emphasis will be placed on the project development life cycle and the importance of testing. Students will be expected to conduct independent research in addition to working collaboratively on projects.

Weekly Zoom sessions will be used for short presentations, Q&A and discussions. In person sessions will be used to present and discuss project progress with the rest of the class and meet with guest experts. At the end of the course, students will have a basic knowledge of machine learning models and libraries and how to use these tools effectively with real-world data.

Prerequisites: Introduction to Python Programming (B+ and above) or sufficient knowledge of Python.