COMPUTER
Artificial Intelligence: Theory and Applications
24ERT503 · S5 · 3 credits
5 modules · Practice & PYQs ready
Syllabus
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⚡ DAY-BEFORE EXAM
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Strategy: High-yield concepts + PYQs + weak areas
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PRIORITY A
Fundamentals to probabilistic reasoning in AI
Why:Foundation module
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PRIORITY A
Introduction to AI
Why:Standard exam coverage
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PRIORITY B
Problem Solving
Why:Standard exam coverage
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PRIORITY B
Introduction to neural networks
Why:Standard exam coverage
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PRIORITY C
Machine Learning
Why:Standard exam coverage
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Modules
5 modulesNotes / Resources
Exam-focused notes are optional context — Continue Learning above works even without them.
Module Progressnot assessed
What this module covers
What it's about
Syllabus module 1: Fundamentals to probabilistic reasoning in AI. Detailed exam-focused notes are not written yet; the official syllabus topics are listed below.
Why it matters in exams
Part of the official Artificial Intelligence: Theory and Applications (24ERT503) — Semester 5. Use the topics below with the AI study prompts while detailed notes are being written.
AI STUDY TOOLSArtificial Intelligence: Theory and Applications → Fundamentals to probabilistic reasoning in AI
≈ 2h of curated content available across this subject.