Artificial Intelligence for GATE Computer Science and IT

Preparing for the GATE Computer Science and IT exam requires a rock-solid grasp of foundational Artificial Intelligence concepts. This text-based course breaks down complex algorithms and logical frameworks into easy-to-digest written lessons. You will transition from basic definitions to solving exam-style problems confidently. By reading detailed explanations and working through step-by-step mathematical proofs, you will build the analytical skills needed to tackle any AI question on the test. What you'll learn: - Understand foundational AI terminology, state-space representation, and production systems. - Apply uninformed search strategies including breadth-first, depth-first, and depth-limited search. - Master informed heuristic search techniques like A* search, greedy best-first search, and hill climbing. - Analyze adversarial search algorithms including minimax and alpha-beta pruning. - Solve propositional and first-order logic problems using resolution and unification. - Practice exam-style questions with comprehensive written solutions and explanations. The course begins with core definitions and state-space representation, then progresses systematically through search algorithms and logic, ending with practice problems designed to reinforce your exam readiness. This course is designed for engineering students and self-learners preparing for the GATE CS and IT exams, requiring only basic discrete mathematics and programming familiarity. Start reading today to master the AI syllabus and boost your exam preparation.