MS Data Science, Analytics and Engineering (Bayesian Machine Learning)
Course Overview
This concentration provides a deep and practical mastery of Bayesian machine learning, preparing you to tackle complex, real-world data challenges. You will learn to build sophisticated probabilistic models and make data-driven decisions under uncertainty. The curriculum is designed to be immediately applicable across diverse fields like finance, biology, engineering, and economics.
Key Program Highlights
- Master advanced techniques like hierarchical modeling, causal inference, and time series analysis.
- Gain hands-on experience with industry-standard tools including Bayesian neural networks and text modeling.
- Learn to manage, analyze, and derive insights from large, noisy, and complex datasets.
- Apply Bayesian thinking to solve high-dimension modeling problems in various domains.
- Benefit from a unique partnership with the School of Mathematical and Statistical Sciences for a rigorous foundation.
Course Overview
This concentration provides a deep and practical mastery of Bayesian machine learning, preparing you to tackle complex, real-world data challenges. You will learn to build sophisticated probabilistic models and make data-driven decisions under uncertainty. The curriculum is designed to be immediately applicable across diverse fields like finance, biology, engineering, and economics.
Key Program Highlights
- Master advanced techniques like hierarchical modeling, causal inference, and time series analysis.
- Gain hands-on experience with industry-standard tools including Bayesian neural networks and text modeling.
- Learn to manage, analyze, and derive insights from large, noisy, and complex datasets.
- Apply Bayesian thinking to solve high-dimension modeling problems in various domains.
- Benefit from a unique partnership with the School of Mathematical and Statistical Sciences for a rigorous foundation.
