Summer 2025 Course Topic: Foundation in Artificial Intelligence Applications
This introductory course provides students from all academic backgrounds with a comprehensive understanding of Artificial Intelligence (AI) through a scientific and applications’ lens.
Students will explore AI's foundational principles, examine its methodologies, and engage in hands-on experimentation. The course emphasizes scientific inquiry, evidence-based analysis, and ethical considerations while providing practical laboratory experience through individual exercises.
- Semester: Summer 2025
- Instructor: Dave Fusco
- Who:
- Students who can use this course as a Social and Behavioral Sciences (GS) General Education course or an elective for any major.
- Undergraduates in any major who are interested in learning about AI, Generative AI, and Agentic AI agents used to provide solutions in all disciplines.
- When: Remote Asynchronous
- Where: Remote Asynchronous
- Credits: 3.0
- General Education: Social and Behavioral Sciences (GS)
- LionPATH Class Number: 8624
This introductory course explores how modern artificial intelligence is transforming business and professional work. Students from all majors will learn about enterprise AI systems, generative AI tools (like large language models and image generators), and AI agents - with a focus on practical applications in their chosen fields. Through hands-on experience with current AI tools, students will develop an understanding of AI's capabilities, limitations, and potential impact on their future careers. No prior programming or technical background required.
Major Assessments (60%)
Final Individual Project (25%)
- Students will develop a detailed proposal for implementing AI solutions in their field of study.
- Includes analysis of tools, potential impacts, limitations, and ethical considerations.
- Culminates in a form of a presentation and/or written report
Midterm Exam (15%)
- Focus on understanding key concepts, use cases, and limitations of different AI technologies
- Mix of multiple choice and short answer questions to assess comprehension
- Include case studies for analysis
Hands-on Labs (20%)
- 5-6 structured labs throughout semester (about 3-4% each)
- Practice with different AI tools (e.g., ChatGPT, DALL-E, Copilot)
- Focus on practical applications and understanding capabilities/limitations
Ongoing Assessments (40%)
AI Explorer Weekly Journal (20%)
- Students document their experiences using various AI tools
- Format: "What I tried" / "What I learned" / "What surprised me"
- Must include specific examples and screenshots of their interactions
- Emphasis on critical thinking about tool effectiveness
Weekly "AI in the Wild" Reports (20%)
- Students find real-world examples of AI use in their field
- Required to use AI tools to help research but must write analysis themselves
- Include reflection on how AI helped their research process
- Short (500 words) but substantive analysis of implications
- For the "AI in the Wild" reports:
- Use AI to help find relevant examples and research
- Use AI to help brainstorm analysis angles
- Students write their own analysis but can use AI for editing/refinement
- Students must include a brief description of how they used AI tools in their research process