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This course builds on foundational concepts from Introduction to Statistical Concepts and Describing Data and focuses on examining relationships and comparing group means in healthcare data. Students will learn to calculate and interpret correlation coefficients, conduct independent sample t-tests and ANOVA, and evaluate the assumptions underlying these techniques. Practice examples using healthcare data will help reinforce the relevance of these tests for everyday decision-making in clinical and research environments.
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This course introduces key statistical concepts and data analysis techniques used in healthcare. Students will learn to classify variables, summarize data, i…
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This course is all about data and how it is critical to the success of your applied machine learning model. Completing this course will give learners the ski…
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This course takes you from understanding the fundamentals of a machine learning project. Learners will understand and implement supervised learning technique…
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This course will give you hands-on FPGA design experience that uses all the concepts and skills you have developed up to now. You will need to purchase a DE1…
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This course can also be taken for academic credit as ECEA 5601, part of CU Boulder’s Master of Science in Electrical Engineering degree. Optical instruments…
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The ultimate destination for a security manager is the Chief Information Security Officer (or Chief Security Officer) a senior executive role responsible for…
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Introduces number-theory based cryptography, basics of quantum algorithms and advanced data-structures. This course can be taken for academic credit as part…
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This course can also be taken for academic credit as ECEA 5600, part of CU Boulder’s Master of Science in Electrical Engineering degree. Optical instruments…
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