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We are in the age of Big Data. Knowing how to handle, manipulate, and interpret data is a critical skill in this modern age, regardless of whether you want to pursue advanced study or find a job in tech or data-intensive fields.
In this course, we will introduce the basic statistical concepts necessary to understand, fit, and choose the best models that describe data. We will also explore machine learning and artificial intelligence methods that are designed to maximize the information you can extract from your dataset and make predictions about unseen data.
Topics covered in this course:
1. Probability and statistical distributions.
2. Frequentist and Bayesian inference.
3. Bayesian parameter estimation using MCMC techniques.
4. Data mining and visualization.
5. Regression and classification.
6. Time-series analysis.
7. Machine learning and neural networks.
Course details:
Lectures will be Tues/Thurs., 2 pm -- 3:20 pm. Pre-requisites may be waived on a case-by-case basis.
For more details, please reach out to Nihan Pol (npol@ttu.edu)
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Posted:
1/2/2025
Originator:
Nihan Pol
Email:
npol@ttu.edu
Department:
Physics
Categories
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