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Learn Applied Analytics, earn certificates with free online courses from Stanford, MIT, University of Pennsylvania, University of Michigan and other top universities around the world. Read reviews to decide if a class is right for you.
Apply analytics to accounting work: assemble financial statement data, build charts in Excel and Tableau, and run correlation, regression, Solver optimization, and clustering.
Test the Moneyball claims with Python: compute on base percentage, slugging, run expectancy matrices and wins above replacement from public MLB datasets.
Explore how athletes' wearable sensors quantify training: internal versus external load, acute-to-chronic workload, and global metrics, using Python on sport team datasets.
Forecast professional game outcomes with logistic and ordered logit models in Python, using team spending data and testing accuracy against Premier League, NBA, NHL and MLB betting odds.
Build an analytics program for an agile product team: test customer hypotheses, run fast demand experiments, track usability continuously, and interface with data science capabilities.
Work hands-on with biomedical data: sequence processing, medical image analysis, probabilistic and network modelling, NLP of clinical notes, process modelling, and graph data linkage.
Work with real electronic health record data: assess clinical data models and quality, identify patient populations, apply clinical NLP, and build predictive models.
Prepare for a career in the growing field of FinTech through this comprehensive program covering in-demand data science and financial technology skills.
Learn how to construct, fit, estimate and compute Bayesian statistical models with the help of OpenBUGS (freely available software)
Analyze stock prices, returns, and risk: build moving average, Holt-Winters, and ARIMA forecasts in R and optimize portfolios using modern portfolio theory.
Learn where clinical data come from, their formats, and ethical and legal limits, while querying a real clinical data set with SQL and analyzing it in R's tidyverse.
Turn raw healthcare data into actionable information: compare administrative, clinical, claims and patient-reported sources, build data models, and address data quality and governance.
Aprenderás a utilizar el método AHP para seleccionar de forma objetiva el mejor jugador para una posición o estimar el valor de su traspaso.
Applies linear algebra to machine learning, signal processing, wireless communications, data analytics, and operations research.
This foundational course offers an extensive overview of business analytics and machine learning, starting with a motivational example to highlight the practical significance of analytics. It delves i
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