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Learn Sports Analytics, earn certificates with paid and free online courses from MIT, University of Michigan, SUNY, Universitat Politècnica de València and other top universities around the world. Read reviews to decide if a class is right for you.
Learn to analyze and predict sports performance using real data from MLB, NBA, NHL, EPL, and IPL in this 30-week course by the University of Michigan. Ideal for sports enthusiasts and Python programmers.
Learn to analyze sports team performance using Python and R in this 6-week course by the University of Michigan. Gain skills in data representation and regression analysis.
Explore sports analytics and wearable technologies with the University of Michigan's 5-week course. Learn to optimize training, prevent injuries, and analyze large datasets using Python.
Explore the application of data analytics in sports law and team management with this 5-week course from the State University of New York. Gain insights into player productivity, fan engagement, and more.
Learn sports analytics with Ken Jee in a 4-5 hour program. Understand NBA data scraping, sports betting, golf stats, and simulate NBA games using Python.
In this introductory level Quest you will gain practical experience on the fundamentals of sports data science using BigQuery. Start your journey by creating a soccer dataset in BigQuery by importing CSV and JSON files. Harness the power of BigQuery with…
Aprenderás a utilizar el método AHP para seleccionar de forma objetiva el mejor jugador para una posición o estimar el valor de su traspaso.
Explore the revolution in sports analytics with the University of Michigan's 5-week course. Learn Python programming for data analysis, calculate baseball stats, and conduct team/player analyses.
Learn to forecast professional sports game results using Python and logistic regression in this 5-week course by the University of Michigan. Explore data analytics, gambling, and related social issues.
Explore supervised machine learning techniques in sports analytics with real-world data in this 4-week course by the University of Michigan. Learn to predict athletic outcomes using Python's sklearn toolkit.
This course presents real-world examples in which quantitative methods provide a significant competitive edge that has led to a first order impact on some of today's most important companies.
Learn how probability, math, and statistics can be used to help baseball, football and basketball teams improve, player and lineup selection as well as in game strategy.
Learn 3 popular sport ranking methods and how to create March Madness brackets with them. Let math make the picks!
A-Z guide on how the game of baseball works including chalkboard-style video lessons, quizzes, and fun videos.
Learn to analyze baseball games visually using PITCHf/x data and ggplot in R. Gain skills in data scraping, plot creation, and vector subsetting in a 3-week course.
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