CSC-150 AI Foundations

AI Foundations introduces students to artificial intelligence tools and practical applications without requiring technical or programming backgrounds. Students learn to effectively use leading AI platforms including ChatGPT, Claude, and specialized tools for text, image, and voice generation. Through hands-on practice with prompt engineering and model comparison using platforms like LM Arena, students develop critical skills in selecting appropriate AI tools, evaluating outputs for accuracy and bias, and integrating AI into their personal and professional workflows. The course emphasizes ethical considerations from the ground up, including privacy, attribution, and responsible AI use. By the end of the course, students can confidently leverage AI tools to enhance productivity, solve problems creatively, and critically assess AI-generated content. No prior AI experience required.

Credits

1

Lecture Contact Hours

1

Lab Contact Hours

0

Other Contact Hours

0

Department

• Computer Science

Grading Scheme

• Letter

SUNY Gen Ed Credit

• No

Semesters Course Will Be Offered

• Fall
• Spring
• Summer
• Winter

Course Learning Outcomes

1. Craft effective prompts to generate high-quality outputs from multiple AI platforms for text, image, and voice applications.
2. Evaluate and select appropriate AI models and tools for specific tasks by comparing capabilities, limitations, and performance across different platforms.
3. Critically assess AI-generated content for accuracy, bias, and reliability, demonstrating understanding of common failure modes including hallucinations and inherent model limitations.
4. Apply ethical frameworks to AI tool usage, including considerations of privacy, data security, attribution, copyright, and responsible deployment in professional contexts.

View Course Outline

CSC 150: AI Foundations

Department

Computer Science

Course Description

AI Foundations introduces students to artificial intelligence tools and practical applications without requiring technical or programming backgrounds. Students learn to effectively use leading AI platforms including ChatGPT, Claude, and specialized tools for text, image, and voice generation. Through hands-on practice with prompt engineering and model comparison using platforms like LM Arena, students develop critical skills in selecting appropriate AI tools, evaluating outputs for accuracy and bias, and integrating AI into their personal and professional workflows. The course emphasizes ethical considerations from the ground up, including privacy, attribution, and responsible AI use. By the end of the course, students can confidently leverage AI tools to enhance productivity, solve problems creatively, and critically assess AI-generated content. No prior AI experience required.

Credit Hours

1

Contact Hours

Lecture	1
Lab	0
Other	0

Grading Scheme

Letter

Semester(s) Course Will Be Offered

Fall, Spring, Summer, Winter

First Year Experience Course

No

Capstone Course

No

Course Learning Outcomes

1. Craft effective prompts to generate high-quality outputs from multiple AI platforms for text, image, and voice applications.
2. Evaluate and select appropriate AI models and tools for specific tasks by comparing capabilities, limitations, and performance across different platforms.
3. Critically assess AI-generated content for accuracy, bias, and reliability, demonstrating understanding of common failure modes including hallucinations and inherent model limitations.
4. Apply ethical frameworks to AI tool usage, including considerations of privacy, data security, attribution, copyright, and responsible deployment in professional contexts.

Topic Outline

1. AI Foundations & Effective Use provides a practical introduction to artificial intelligence tools and applications for students with no prior AI experience. This course demystifies AI technology and builds essential skills for using AI effectively, ethically, and critically in personal and professional contexts.

2. Learners will explore:

3.

4. AI fundamentals - Understanding what AI actually is, how large language models work, and the current AI landscape

5.

6. Prompt engineering - Crafting effective prompts to generate high-quality outputs from leading AI platforms

7.

8. Model comparison - Using tools like LM Arena to evaluate and select appropriate AI models for specific tasks

9.

10. Multimodal AI applications - Working with text generation (ChatGPT, Claude, Gemini), image creation (Midjourney, DALL-E, Stable Diffusion), voice AI, and combined modalities

11.

12. Critical evaluation - Identifying hallucinations, bias, and limitations in AI-generated content

13.

14. Ethics and responsible use - Privacy considerations, attribution, copyright, and building skills to assess AI outputs critically

15.

16.