UofU Data Science Courses

Machine Learning - Lecture 19

Dive into advanced data science concepts through comprehensive coverage of machine learning principles, algorithms, and practical applications in this university-level lecture.

• YouTube
• 1 hour 14 minutes
• On-Demand
• Free Video

Machine Learning Fundamentals - Lecture 10

Dive into advanced machine learning concepts and techniques through comprehensive coverage of key algorithms, theoretical foundations, and practical applications in data science.

• YouTube
• 1 hour 19 minutes
• On-Demand
• Free Video

Machine Learning Debug Tutorial - Fall 2023

Master essential debugging techniques for machine learning algorithms, focusing on practical troubleshooting methods and common error resolution in ML development.

• YouTube
• 43 minutes
• On-Demand
• Free Video

Machine Learning Fundamentals - Lecture 1

Dive into foundational machine learning concepts, algorithms, and theoretical frameworks in this comprehensive first lecture of advanced data science studies.

• YouTube
• 1 hour 11 minutes
• On-Demand
• Free Video

Introduction to Machine Learning Model Explanations and Interpretability

Explore key concepts in data science explanations, from gradient-based highlighting to contrastive editing, covering essential techniques for understanding and interpreting complex models.

• YouTube
• 1 hour 21 minutes
• On-Demand
• Free Video

Probability and Statistics: A Comprehensive Review - Lecture 18

Master essential probability and statistics concepts, from basic probability and random variables to hypothesis testing and confidence intervals in this comprehensive semester review.

• YouTube
• 1 hour 51 minutes
• On-Demand
• Free Video

Probabilistic Machine Learning - Lecture 28

Dive into advanced data science concepts and methodologies through comprehensive lecture materials from the University of Utah's graduate-level computer science program.

• YouTube
• 43 minutes
• On-Demand
• Free Video

Machine Learning Practical Concerns and Societal Impacts - Lecture 28

Explore practical neural network implementation challenges and gain valuable insights into building ethical, socially responsible machine learning systems.

• YouTube
• 1 hour 21 minutes
• On-Demand
• Free Video

Neural Networks and Backpropagation Algorithm - Lecture 27

Dive into the backpropagation algorithm and advanced neural network concepts, mastering fundamental techniques for training deep learning models effectively.

• YouTube
• 1 hour 20 minutes
• On-Demand
• Free Video

Probabilistic Machine Learning - Lecture 27

Dive into advanced data science concepts through comprehensive lecture coverage of key theoretical and practical aspects in modern data analysis and machine learning.

• YouTube
• 1 hour 20 minutes
• On-Demand
• Free Video

Linear Regression and Parameter Estimation in R - Lecture 17

Master linear regression techniques in R while exploring parameter estimation and random variable estimators through hands-on statistical analysis and practical applications.

• YouTube
• 1 hour 20 minutes
• On-Demand
• Free Video

Probabilistic Machine Learning - Lecture 26

Dive into advanced data science concepts through comprehensive lecture coverage of key theoretical and practical aspects in this graduate-level academic session.

• YouTube
• 1 hour 21 minutes
• On-Demand
• Free Video

Confidence Intervals and Hypothesis Testing with R Examples - Lecture 16

Master statistical analysis through confidence intervals and hypothesis testing, with practical R programming examples for real-world data interpretation and decision-making.

• YouTube
• 1 hour 19 minutes
• On-Demand
• Free Video

Machine Learning Fundamentals - Lecture 4

Dive into advanced machine learning concepts and algorithms through comprehensive coverage of key theoretical foundations and practical implementations in data science.

• YouTube
• 1 hour 22 minutes
• On-Demand
• Free Video

Uncertainty, Prompting, and Chain-of-Thoughts in Large Language Models - Part 2

Dive into advanced AI concepts including temperature scaling, Bayesian calibration, prompt-based finetuning, and chain-of-thought techniques for more reliable and explainable language models.

• YouTube
• 1 hour 21 minutes
• On-Demand
• Free Video