37. Basic Probability Notation in AI | Artificial Intelligence | CSE

This lecture is a part of a lecture series given by Ms Ishika on Artificial intelligence for Computer Science Engineering students at Binary Institute. Description In this video, we explore the concept of Basic Probability Notation in Artificial Intelligence, an essential foundation for understanding uncertainty in AI systems. Probability plays a crucial role in decision-making, reasoning, and prediction, especially when dealing with incomplete or uncertain data. We begin by introducing fundamental probability terms such as sample space, events, and outcomes. Then, we move on to key notations including prior probability, conditional probability, joint probability, and marginal probability. Each concept is explained in a simple and clear manner, making it easy for students of Computer Science and Engineering to grasp. This video is especially useful for B.Tech CSE students and anyone preparing for exams or interviews in Artificial Intelligence. Understanding these notations is a stepping stone toward advanced topics like Bayesian networks, probabilistic reasoning, and machine learning. Watch till the end to build a strong base in probability concepts used in AI. #ArtificialIntelligence #Probability #AIConcepts #CSE #MachineLearning #EngineeringStudents #ProbabilisticReasoning #BTech #AIStudies