UofU Data Science Courses

Prompting for Evaluation of Free-Text Explanations - Part 2

Dive into advanced techniques for evaluating free-text explanations in AI prompting, focusing on methodologies and practical applications for data science analysis.

• YouTube
• 1 hour 22 minutes
• Self-Paced
• Free Video

Machine Learning Fundamentals - Lecture 5

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 22 minutes
• Self-Paced
• 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
• Self-Paced
• 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
• Self-Paced
• Free Video

Machine Learning Fundamentals - Probability and Random Variables - Lecture 3

Dive into fundamental concepts of data science, covering probability theory, random variables, and exploratory data analysis through hands-on projects and interactive lectures.

• YouTube
• 1 hour 15 minutes
• Self-Paced
• Free Video

Pretrain-Finetune and Uncertainty Estimation in Machine Learning - Part 1

Dive into advanced machine learning concepts, from masked language modeling and pretrained vision models to uncertainty estimation and probability calibration techniques.

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

Machine Learning Fundamentals - Lecture 2

Dive into machine learning fundamentals with a comprehensive exploration of decision trees, data classification techniques, and algorithmic approaches to pattern recognition.

• YouTube
• 1 hour 4 minutes
• Self-Paced
• Free Video

Data Preparation and Transformer Models - Introduction to Text and Image Processing

Master data preparation techniques for transformers, including text and image processing, and understand the fundamentals of transformer architecture and pretraining methods.

• YouTube
• 1 hour 8 minutes
• Self-Paced
• 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
• Self-Paced
• 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
• Self-Paced
• 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
• Self-Paced
• 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
• Self-Paced
• 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
• Self-Paced
• 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
• Self-Paced
• 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
• Self-Paced
• Free Video