Revised 03/2025

CSC 295 - Computer Science Topics in: Advanced Artificial Intelligence (3 CR.)

Course Description

This course provides advanced concepts and applications of artificial intelligence with uncertain knowledge reasoning, algorithm design for machine learning, natural language processing, computer vision and robotics. The course will facilitate problem solving and applications in a variety of areas. Basic knowledge of programming (Java preferred), and problem-solving concepts are recommended. Lecture 3 hours. Total 3 hours per week

General Course Purpose

CSC 295 is intended as an elective course for the AS in Computer Science, and as requirements for Certificate in Computer Science program.

Course Prerequisites/Corequisites

CSC 222is recommended.

Course Objectives

Upon completing the course, the student will be able to:

  • Review fundamental concepts of artificial intelligence.
  • Explain concepts of quantifying uncertainty.
  • Define probabilistic reasoning and probabilistic reasoning over time.
  • Explore probabilistic programming.
  • Explain simple and complex decision making using artificial intelligence concepts.
  • Explain multiagent decision making.
  • Explain learning from examples and learning probabilistic models.
  • Explain deep learning and reinforcement learning.
  • Define concepts of natural language processing and deep learning for natural language processing.
  • Define fundamental concepts of robotics.
  • Explain generative AI concepts, solving applications in a variety of domains.
  • Solve problems involving advanced concepts of artificial intelligence.

Major Topics to Be Included

  • Review fundamental concepts of artificial intelligence
  • Quantifying uncertainty
  • Probabilistic programming
  • Probabilistic reasoning and probabilistic reasoning over time
  • Making simple and complex decisions
  • Multiagent decision making
  • Learning from examples and probabilistic models
  • Deep learning and reinforcement learning
  • Natural language processing and deep learning for natural language processing
  • Generative AI Methods and Applications
  • Robotics