Artificial Intelligence (MCA)

Intelligent agents, search techniques, knowledge representation, reasoning, planning and an introduction to machine learning.

6 महीनेअवधि 5Chapters26टॉपिक

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सिलेबस · पाठ्यक्रम

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01Unit 1: Introduction and Intelligent Agents 5 टॉपिक

Definition, history and applications of AI
Turing test
Agents and environments; PEAS description
Types of environments
Agent types: simple reflex, model-based, goal-based, utility-based, learning

02Unit 2: Problem Solving by Search 6 टॉपिक

Problem formulation and state space
Uninformed search: BFS, DFS, uniform cost, iterative deepening
Informed search: greedy best-first, A* and heuristics
Local search: hill climbing, simulated annealing, genetic algorithms
Adversarial search: minimax and alpha-beta pruning
Constraint satisfaction problems

03Unit 3: Knowledge Representation and Reasoning 5 टॉपिक

Propositional logic and inference
First-order predicate logic
Unification and resolution
Forward and backward chaining
Semantic networks, frames and ontologies

04Unit 4: Uncertainty and Planning 5 टॉपिक

Probability basics and Bayes' rule
Bayesian belief networks
Fuzzy sets and fuzzy logic
Classical planning and STRIPS
Expert systems: architecture and examples

05Unit 5: Learning and Applications 5 टॉपिक

Forms of learning: supervised, unsupervised, reinforcement
Decision tree learning
Artificial neural networks basics
Reinforcement learning basics
Natural language processing and robotics overview

परिचय

आप यह कर पाएँगे

Define AI and describe intelligent agents and their environments using PEAS
Solve problems with uninformed, informed, local and adversarial search
Represent knowledge in propositional and first-order logic and apply resolution
Reason under uncertainty using Bayes' rule, Bayesian networks and fuzzy logic
Explain planning, expert systems and basic natural language processing
Describe supervised, unsupervised and reinforcement learning

यह किसके लिए है

MCA students of Semester 3 (AKTU, Lucknow)
Students preparing for UGC-NET / GATE and AI-related job interviews

आपको क्या चाहिए

Data structures (graphs, trees) and basic probability

सवाल

Which syllabus does this Artificial Intelligence course follow?

It follows the AKTU (Lucknow) MCA syllabus for Semester 3. If your own university's syllabus differs, the centre follows your university's syllabus and unit order.

Is programming needed for this paper?

The theory paper has no coding, but the Artificial Intelligence Lab uses Python and the centre teaches both together.

How are students tested at the centre?

Unit-wise MCQ tests, numerical / problem practice, previous AKTU question papers and a final mock paper before the semester exam.