UofU Data Science Courses

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
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• Free Video

Introduction to Neural Networks - Lecture 25

Explore neural networks' fundamental concepts, structure, and prediction mechanisms while learning essential training approaches for building effective machine learning models.

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

Gradient-Based Input Attribution Methods and Their Applications

Explore gradient-based input attribution methods, from fundamental concepts to practical applications, limitations, and advanced extensions in machine learning model interpretability.

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

Machine Learning Fundamentals - Lecture 7

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

Machine Learning Fundamentals - Lecture 6

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

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
• On-Demand
• 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
• On-Demand
• Free Video

Machine Learning Fundamentals - Lecture 8

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 14 minutes
• On-Demand
• Free Video

Matrix Completion and PageRank in Data Mining - Spring 2023

Dive into matrix completion techniques and PageRank algorithms, exploring fundamental concepts for data mining and graph analysis applications.

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

Bayesian Learning and Maximum Likelihood Methods - Lecture 23

Explore probabilistic learning criteria through maximum a posteriori and maximum likelihood examples, enhancing your understanding of Bayesian learning fundamentals.

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

Learning as Loss Minimization in Machine Learning - Lecture 23

Delve into the fundamental concept of learning as optimization, exploring how empirical risk minimization forms the foundation of machine learning algorithms.

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

Stochastic Gradient Descent for Support Vector Machines - Lecture 22

Dive into stochastic gradient descent algorithms and their application in optimizing Support Vector Machines through practical implementation techniques and mathematical foundations.

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