ARTIFICIAL INTELLIGENCE (MCA-205)
Program: Master of Computer Applications
Category: Professional Core Course
Semester: 2
Credits: 4
L-T-P: 4- 0- 0
Description
The "Artificial Intelligence" syllabus introduces key concepts in AI, including search algorithms, knowledge representation, and reasoning. It covers machine learning techniques, such as supervised and unsupervised learning, and neural networks. Students explore natural language processing, robotics, and expert systems. Topics also include decision-making, planning, and problem-solving under uncertainty. The course aims to provide a solid foundation in both theoretical and practical aspects of AI.
Instructor

Ms. Arti Kotru

Associate Professor
Department Of Computer Applications
Course Outcomes
  • Assimilate the fundamental concepts in Artificial Intelligence
  • Analyze a real-world problem for implementation and understand the dynamic behavior of a system.
  • Apply techniques in applications which involve perception, reasoning and learning.
  • Develop a practical skills in designing and implementing multi-agent systems and genetic algorithms
  • Use different machine learning techniques to design AI machine and enveloping applications for real world Problems.
Resources
Course Handout Lesson Plan Syllabus
Evaluation Scheme
Assignment 10
Attendance 10
Sessional 20
Total Internal 40
Total External 60
Overall Total 100