Fifth Semester · BCA 302
Artificial Intelligence Notes
A dedicated BCA World study page for this subject, aligned to the TU BCA 2025 curriculum units.
How to study this subject
For each unit, learn the definition, understand the process, practise one example, and finish by explaining the concept in your own words. Use the model questions after completing the unit notes.
Unit-by-unit notes
01
AI foundations, agents, problem spaces, and state-space search
Revise the definition, components, workflow, common examples, and practical use of ai foundations, agents, problem spaces, and state-space search. Relate it to a small problem or case study from Artificial Intelligence.
- Define the key terms and identify the main components.
- Draw or describe the workflow, architecture, formula, or process where relevant.
- Connect the idea to a practical BCA example and revise common advantages or limitations.
02
Uninformed, informed, adversarial, and constraint-satisfaction search
Revise the definition, components, workflow, common examples, and practical use of uninformed, informed, adversarial, and constraint-satisfaction search. Relate it to a small problem or case study from Artificial Intelligence.
- Define the key terms and identify the main components.
- Draw or describe the workflow, architecture, formula, or process where relevant.
- Connect the idea to a practical BCA example and revise common advantages or limitations.
03
Knowledge representation, logic, inference, and reasoning under uncertainty
Revise the definition, components, workflow, common examples, and practical use of knowledge representation, logic, inference, and reasoning under uncertainty. Relate it to a small problem or case study from Artificial Intelligence.
- Define the key terms and identify the main components.
- Draw or describe the workflow, architecture, formula, or process where relevant.
- Connect the idea to a practical BCA example and revise common advantages or limitations.
04
Machine-learning concepts, classification, clustering, and evaluation
Revise the definition, components, workflow, common examples, and practical use of machine-learning concepts, classification, clustering, and evaluation. Relate it to a small problem or case study from Artificial Intelligence.
- Define the key terms and identify the main components.
- Draw or describe the workflow, architecture, formula, or process where relevant.
- Connect the idea to a practical BCA example and revise common advantages or limitations.
05
Neural/fuzzy concepts, natural language, and AI applications and ethics
Revise the definition, components, workflow, common examples, and practical use of neural/fuzzy concepts, natural language, and ai applications and ethics. Relate it to a small problem or case study from Artificial Intelligence.
- Define the key terms and identify the main components.
- Draw or describe the workflow, architecture, formula, or process where relevant.
- Connect the idea to a practical BCA example and revise common advantages or limitations.
Model questions for BCA 302
Short answerDefine ai foundations, agents, problem spaces, and state-space search and mention two important uses.
Define ai foundations, agents, problem spaces, and state-space search and mention two important uses. Answer using a definition, structured explanation, relevant example, and conclusion.
Long answerExplain uninformed, informed, adversarial, and constraint-satisfaction search with a suitable diagram, example, or step-by-step method.
Explain uninformed, informed, adversarial, and constraint-satisfaction search with a suitable diagram, example, or step-by-step method. Answer using a definition, structured explanation, relevant example, and conclusion.
Practical / applicationApply knowledge representation, logic, inference, and reasoning under uncertainty to solve a small Artificial Intelligence problem. State your assumptions and conclusion.
Apply knowledge representation, logic, inference, and reasoning under uncertainty to solve a small Artificial Intelligence problem. State your assumptions and conclusion. Answer using a definition, structured explanation, relevant example, and conclusion.