UofU Data Science Courses

DPO and Reasoning Language Models

Explore Direct Preference Optimization techniques and reasoning capabilities in large language models through comprehensive analysis and practical applications.

• YouTube
• 1 hour 21 minutes
• Self-Paced
• Free Video

Markov Chains - From Probability Transition Matrix to Ergodic Properties and Algorithms - L24

Explore Markov chains through probability transition matrices, ergodic properties, and limiting states. Master 4 key algorithms including eigenvalue methods and random walks for data science.

• YouTube
• 1 hour 23 minutes
• Self-Paced
• Free Video

Outlier Detection - Methods and Robust Estimation Techniques - L20

Discover robust methods for identifying and handling outliers in data science, from residual-based detection to advanced techniques like eigenvector pruning and geometric medians.

• YouTube
• 1 hour 21 minutes
• Self-Paced
• Free Video

Foundations of Data Analytics - Welcome and Syllabus - L1

Discover the foundations of data analysis through syllabus review and essential Quiz 0 preparation materials in this introductory session.

• YouTube
• 20 minutes
• Self-Paced
• Free Video

Multi-Linear and Polynomial Regression - L12

Master multi-dimensional linear regression and polynomial regression techniques using optimal least-squares solutions and closed-form mathematical approaches.

• YouTube
• 1 hour 21 minutes
• Self-Paced
• Free Video

Model Diffing with Crosscoders - CS 6966 Interpretability of LLMs Spring 2026

Explore model diffing techniques using crosscoders to understand differences between large language models and enhance interpretability methods.

• YouTube
• 44 minutes
• Self-Paced
• Free Video

Utah CS 6966 Interpretability of LLMs - Probing Part 2 - Spring 2026

Delve into advanced probing techniques for understanding how large language models process and represent information internally.

• YouTube
• 33 minutes
• Self-Paced
• Free Video

Linear Algebra Review Part 1 - Vectors, Matrices, and Multiplication - Lecture 8

Master essential linear algebra concepts including vectors, matrices, addition, multiplication, and geometric interpretations for data analysis.

• YouTube
• 1 hour 21 minutes
• Self-Paced
• Free Video

Interpretability of LLMs - Superposition

Explore superposition in large language models and understand how neural networks represent multiple features in fewer dimensions through interpretability techniques.

• YouTube
• 1 hour 10 minutes
• Self-Paced
• Free Video

Interpretability of LLMs - SAE Use Cases and Training Advances

Explore Sparse Autoencoders (SAE) applications and training improvements for interpreting large language models through advanced computational techniques.

• YouTube
• 1 hour 19 minutes
• Self-Paced
• Free Video

Graph Embeddings - MDS, Laplacians, and Graph Neural Networks - L23

Explore graph embeddings through MDS, Laplacians, and Graph Neural Networks while examining the ethics of embedding technologies in data science applications.

• YouTube
• 48 minutes
• Self-Paced
• Free Video

Privacy - K-Anonymity, L-Diversity, T-Closeness, and Differential Privacy - L22

Explore privacy protection methods including k-anonymity, l-diversity, t-closeness, and differential privacy mechanisms for safeguarding sensitive data.

• YouTube
• 1 hour 23 minutes
• Self-Paced
• Free Video

LLM-as-Judge - Instruction Finetuning and Supervised Fine-Tuning

Explore LLM-as-judge techniques and instruction finetuning methods for supervised fine-tuning in this comprehensive data science presentation.

• YouTube
• 1 hour 20 minutes
• Self-Paced
• Free Video

Foundations of Data Analysis - Bayesian Inference - L5

Explore Bayesian inference through MAP estimation with normal priors and error distributions, discovering how log-posterior becomes a weighted average of data and prior knowledge.

• YouTube
• 59 minutes
• Self-Paced
• Free Video

Interpretability of LLMs - Evaluating SAE Feature Descriptions

Explore methods for evaluating Sparse Autoencoder feature descriptions in large language models through practical interpretability techniques.

• YouTube
• 1 hour 12 minutes
• Self-Paced
• Free Video