Artificial Intelligence is one of the trending fields in computer science. It deals with building complex machines that are capable of performing human-like tasks. The artificial intelligence course syllabus is different for different courses, colleges and institutes, but each course focuses on some common subjects that give an overview of artificial intelligence. 

This course covers  the basic concepts of Artificial Intelligence syllabus for B. Tech, BCA, MCA students.

It will cover the complete syllabus and will help understanding AI.

The topics covered are as follows:

1. AI vs ML vs DL vs DS

2. Introduction to Intelligent Agents.

3. Simple Reflex Agents.

4. Model Based Reflex Agent.

5. Goal Based Agent.

6. Utility Based Agent.

7. Problem Solving.

8. Uninformed vs Informed Searching.

9. BFS and DFS

10. Heuristic Search and Function.

11. Best First Search.

12. Hill Climbing

13. Constaint Satisfaction Problem.

14. Iterative Deepening Search.

15. Predicate Logic.

16. Propostional Logic.

17. Inference.

The course introduces the variety of concepts in the field of artificial intelligence. It discusses the philosophy of AI, and how to model a new problem as an AI problem. It describes a variety of models such as search, logic, Bayes nets, and MDPs, which can be used to model a new problem. It also teaches many first algorithms to solve each formulation. The course prepares a student to take a variety of focused, advanced courses in various subfields of AI.

This course will introduce the basic ideas and techniques underlying the design of intelligent computer systems. A specific emphasis will be on the statistical and decision-theoretic modeling paradigm.