Introduction to Artificial Intelligence

Course Title: Introduction to Artificial Intelligence

Course Code: CS-AI101

Department: Computer Science

Course Description:

This course provides a comprehensive overview of artificial intelligence principles and techniques. Students will explore core concepts, including machine learning, neural networks, natural language processing, and robotics. The course emphasizes real-world applications and ethical considerations in AI development.

Learning Outcomes:

• Understand fundamental AI concepts and methodologies.
• Develop basic machine learning models and algorithms.
• Analyze and implement AI-driven solutions for practical problems.
• Evaluate ethical implications of AI technologies in society.

Prerequisites:

• Basic understanding of programming (CS-Intro101)
• Foundation in mathematics, especially linear algebra and statistics

Course Outline:

1. Introduction to AI: History, Definitions, and Applications
2. Problem Solving and Search: Algorithms and Strategies
3. Machine Learning Basics: Supervised and Unsupervised Learning
4. Neural Networks: Deep Learning Foundations
5. Natural Language Processing: Text Analysis and Understanding
6. Robotics and Computer Vision: Integration and Interfacing
7. Ethics in AI: Responsible AI Development

Assessment Methods:

• Assignments and Labs: 40%
• Midterm Exam: 20%
• Project Work: 30%
• Participation: 10%

Schedule:

• Lectures: Mondays and Wednesdays, 10:00 AM – 11:30 AM
• Labs: Fridays, 1:00 PM – 3:00 PM

Contact Information:

For inquiries, please contact the Computer Science Department at [email protected] .

Resources:

• Recommended Textbook: “Artificial Intelligence: A Modern Approach” by Stuart Russell and Peter Norvig
• Additional readings and resources will be provided on the course portal.

Note: This course is designed for students with a genuine interest in AI and its applications, preparing them for advanced studies and careers in the field.