Artificial Intelligence
Course Description
Summary
How can we create machines that think, learn, and solve problems? This course explores the fascinating field of artificial intelligence (AI), introducing the fundamental concepts, techniques, and ethical considerations that drive this rapidly evolving discipline.
Building upon your programming knowledge, you will explore key AI paradigms including search algorithms, evolutionary algorithms, swarm intelligence, and machine learning. You will implement AI solutions to real-world problems, and gain an understanding of how to think about contemporary AI development.
This course balances theoretical foundations with practical applications, and encourages critical thinking about both the capabilities and limitations of artificial intelligence. You will develop technical skills valuable across a variety of domains. By the end of the course, you will understand AI's core principles and possess the ability to design, implement, and evaluate basic AI systems.
Topics include: search algorithms, evolutionary algorithms, swarm intelligence, machine learning
Evaluation will be based on active engagement, a midterm, and a comprehensive final examination.
Learning Outcomes
- Apply fundamental AI search algorithms to develop solutions for complex problem domains.
- Implement and evaluate evolutionary algorithms and swarm intelligence techniques to solve optimization problems.
- Develop machine learning models to address real-world classification and pattern recognition tasks.
- Compare and evaluate different AI paradigms to determine appropriate approaches for specific problem domains.
Prerequisites
One of CS4384, CS4382, CS4110, or Data Structures and Algorithms.
Please contact the faculty member : darcyotto@bennington.edu