Course Description
An introduction to artificial intelligence as a human endeavor. Presents foundational concepts and techniques of AI, discusses current applications as well as risks and benefits of AI-based technologies, and provides hands on experience using contemporary tools.
Athena Title
Thinking Machines
Grading System
A - F (Traditional)
Student Learning Outcomes
- Students will be able to explain the basic concepts and principles of artificial intelligence.
- Students will be able to use AI techniques and tools to analyze and solve problems.
- Students will be able to explain the ethical issues and societal impacts created by AI technologies.
- Students will be able to evaluate the performance and quality of AI-based solutions.
Topical Outline
- 1) Introduction to AI: Definitions and goals; subfields of AI; historical milestones
- 2) AI in Practice: AI applications in different fields (humanities, social sciences, STEM)
- 3) AI and Society: Ethical issues in AI; Impacts of AI on society
- 4) Data, Computation, and Algorithms: Data types; structured vs. unstructured data; the nature of computation; introduction to contemporary tools
- 5) AI Modelling: Types of models and modelling formalisms; models in machine learning
- 6) Machine Learning: Supervised, unsupervised, and reinforcement learning; selected machine learning frameworks; evaluation of models
- 7) The Current and Future AI Landscape: neural networks, large language models, generative AI; the prospect of artificial general intelligence
Institutional Competencies
Analytical Thinking
The ability to reason, interpret, analyze, and solve problems from a wide array of authentic contexts.
Critical Thinking
The ability to pursue and comprehensively evaluate information before accepting or establishing a conclusion, decision, or action.
Social Awareness & Responsibility
The capacity to understand the interdependence of people, communities, and self in a global society.
