Intermediate Machine Learning

This 10-week course will cover the theory and application of modern machine learning techniques with a special focus on neural networks, deep learning, and transformers. Students will be introduced to the foundational algorithms and architectures behind modern AI systems. Throughout the course students will also get practical exposure to the application of modern methods. There will also be an emphasis throughout the course on how these methods can be practically deployed in policymaking and the pitfalls associated with their use. The course will conclude with a discussion of how policy can affect AI development.

Upon completion of this course, a student should understand:

• The mechanics behind key ML algorithms and architectures
• How modern AI systems function
• Whether an AI system is suitable for a specific use case and why, and
• How modern AI systems can be deployed in policymaking.