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2025-2026_College Catalog
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CIS 251 - Artificial Intelligence Fundamentals
Credits: 4
Lecture: 4
Lab: 0
This course will provide an introduction into fundamental Artificial Intelligence (AI) concepts including the history of AI, current technologies and applications, theoretical concepts surrounding AI, prompt engineering for AI interfaces and ethics surrounding the AI paradigm.
Course Outcomes:
Students will be able to:
1. Describe what is AI and what’s not AI, the history of AI, and its evolution over time.
2. Analyze current trends in AI by correlating them with other technologies like IoT, Big Data, and 5G.
3. Identify 3 common domains of AI (Natural Language Processing, Computer Vision, and Statistical Data) based on the type of underlying data.
4. Examine typical steps involved in an AI Project through the AI Project Cycle.
5. Value ethical concerns around AI and examine the societal impact AI could have.
6. Describe basic concepts and models encountered in Machine Learning and Deep Learning such as Supervised Learning, Unsupervised Learning, Neural Networks, Reinforcement Learning, etc.
7. Classify different kinds of data available into structured & unstructured based on the underlying quality of the dataset.
8. Examine common no-code tools available for AI Project Building and develop a use case using no-code tools in each domain of AI.
9. Interpret the future of AI, based on upcoming technological trends.
Prerequisite(s): CIS 120
Grading Option: Letter Grade Only
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