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Showing 51–60 of 60 items
Use Python and sports datasets to explore team performance and become a hands-on producer of sports analytics.
Deepen your understanding of C programming and build portable, efficient algorithms using types, operators, recursion, and preprocessing.
Dive into the C programming language and its legacy while comparing syntax and structures with Python.
Analyze athletic performance and recovery using wearable tech, physiological principles, and Python programming on sports datasets.
Master debugging techniques using tools and unit testing to quickly identify, fix, and prevent programming errors in Python.
Learn how Django uses models and ORM to interact with databases, while building skills in SQL, data relationships, and object-oriented programming.
Learn how high-level programming languages work by building data structures and managing memory efficiently using the C language.
Learn to gather, manage, and visualize data using Python and SQL to answer high-level questions and draw meaningful insights.
Use Python to analyze baseball performance data and explore the evolution of Moneyball-era statistics through hands-on coding.
In this video, Kevyn Collins-Thompson, Associate Professor of Information and Electrical Engineering and Computer Science, speaks on what machine learning is and why it is important to data science, h
