Probabilistic Modeling | Data Science | Machine Learning

Comprehensive course on probabilistic modeling techniques, including Bayesian networks and Markov models, for data analysis and decision-making. Taught by experienced faculty at the University of Utah.

Introduction

This course covers the fundamentals of probabilistic modeling, including topics such as Bayesian networks, Markov models, and other probabilistic techniques for data analysis and decision-making.

Highlights

• Comprehensive coverage of probabilistic modeling techniques
• Hands-on experience with real-world data and applications
• Taught by experienced faculty from the University of Utah

Recommendation

This course is recommended for students and professionals interested in data science, machine learning, and decision-making under uncertainty. It provides a solid foundation in probabilistic modeling and its applications across various domains.

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