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Learn Predictive Modeling, 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.
Develop practical data science skills using MATLAB for visualization, analysis, and modeling. Learn to process data, engineer features, and apply machine learning techniques across various industries without becoming a full-time developer.
Learn to optimize supply chains using analytics, forecasting, inventory management, network design, and decision-making under uncertainty. Gain practical skills for strategic planning and operational efficiency.
En este curso conocerás los fundamentos del aprendizaje automático y como crear modelos de predicción, regresión y clasificación con ayuda de Python. Explorarás problemas de clasificación, regresión, series de tiempo, agrupamiento y sistemas expertos.
Gain hands-on experience with big data tools and systems. Learn to organize, analyze, and interpret data for better business decisions. Apply insights to real-world problems through predictive modeling and graph analytics.
This course will teach you how to start from scratch in understanding and paying attention to what is important in the data and how to answer questions about data.
In this course, we introduce the characteristics of medical data and associated data mining challenges on dealing with such data. We cover various algorithms and systems.
Explore AI-driven prediction of COVID-19 resource utilization using fusion modeling, combining patient history and current indicators for efficient healthcare planning and allocation.
Interactive imitation learning for robots: tackling feedback-driven covariate shift and predicting human intent using graph neural networks, with applications in self-driving vehicles.
Exploring stability of radiomics features in brain tumor segmentation and impact on predictive models. Investigates how stable, discriminatory features lead to generalizable radiogenomics for tumor characterization.
Learn to create quantitative models for informed decision-making in complex, uncertain situations. Develop skills in optimization, risk management, and predictive modeling to make data-driven choices in various business scenarios.
Analyze binary outcomes, compare proportions, fit logistic regressions, make predictions, and assess model quality using R. Gain practical skills for health data analysis through lectures and guided coding.
Learn to organize, visualize, and analyze health data using R for statistical modeling, linear regression, and logistic regression to make data-informed decisions in public health.
Explore AI's fundamentals, debunk myths, and gain strategies for meaningful discussions about its societal impact. Develop critical thinking skills to navigate AI's role in various fields.
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 to use classification predictive models to solve business problems involving non-numeric data.
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