Introduction to Applied Machine Learning

Description from DukeHub

Introduction to machine learning with software and applications. Tabular data, computer vision, human language, reinforcement learning, deep learning with artificial neural networks, generative artificial intelligence such as large language models and image generation models. Prerequisite: Computer Science 201. Recommend prerequisite: Math 111L or equivalent.

Skills

• programmingdepartment: COMPSCI
• ai and machine learningdescription: "machine learning" and 5 more

AI-resilient: 0 of 5 0/5

• No: Physical, lab or field work
• No: Live work with people
• No: Judgment someone is accountable for
• No: A craft you practice with your hands or body
• No: Small, in-person format

The checks lean on Microsoft Research, Working with AI (2025), which found generative AI applies least to physical work and hands-on work with people. A signal, not a promise. How the score works

More in COMPSCI

• Introduction to Computer Science COMPSCI 101L
• Data Structures and Algorithms COMPSCI 201
• Introduction to Computer Systems COMPSCI 210D
• Everything Data COMPSCI 216
• Discrete Math for Computer Science COMPSCI 230
• Computer Architecture COMPSCI 250D

All COMPSCI courses · All of Undergraduate