# 6.S090 Probabilistic Computing > *"How do we build AI systems that reason about uncertainty?"* Probabilistic Computing explores how to build intelligent systems using probabilistic programming, Bayesian inference, and automated reasoning. ## 🎯 Key Topics - Probabilistic programming languages (Gen.jl) - Bayesian inference algorithms (MCMC, SMC) - Generative models and simulation - Automated model formalization - AI for scientific discovery ## 🔗 Battlefield: 🐅 CompBayes Core training in Bayesian methods, uncertainty quantification, and computational inference for decision-making. ← [[Sources/Courses]]