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Duke University is a world-renowned private research university located in Durham, NC. Its commitment to interdisciplinary learning and collaborative research helps shape the futures of its students and communities.
In this course, you will discover the organization of the neural systems in the brain and spinal cord that mediate sensation, motivate bodily action, and integrate sensorimotor signals with memory, emotion and related faculties of cognition.
This course provides the basic biology you need to understand all of these issues better, tries to clarify some misconceptions, and tries to prepare students for future, more advanced coursework in Biology (and especially evolutionary genetics).
In this course, students learn to recognize and to apply the basic concepts that govern integrated body function (as an intact organism) in the body's nine organ systems.
Build predictive models in Excel: score credit card applicants with binary classification and AUC, quantify uncertainty with entropy, and forecast with linear regression and confidence intervals.
Dog Emotion and Cognition will introduce you to the exciting new study of dog psychology, what the latest discoveries tell us about how dogs think and feel about us, and how we can use this new knowledge to further strengthen our relationship with our be…
You will gain a foundation for college-level writing valuable for nearly any field.
Build interactive web pages with HTML, CSS, and JavaScript: write functions, for loops, and conditionals, and create a site where users upload and filter images.
Trace how the brain builds a sense of space: depth cues, receptive fields and cortical maps, sound localization, reference frames, vestibular navigation, place cells and grid cells.
Learn to code in Java with BlueJ: write methods, loops and conditionals, manipulate strings to find genes and links, and analyze CSV data with Apache Commons CSV.
Apply Bayes' rule to turn priors into posteriors: work with conjugate families, credible intervals, Bayes factors, and Bayesian regression with model averaging in R.
Master the notation and algebra behind data science: set theory and Venn diagrams, sigma notation, graphing functions, derivatives, exponents and logarithms, and Bayes' theorem.
Learn to name compounds, convert grams to moles, balance equations, and solve stoichiometry problems involving solubility rules, acid-base and redox reactions.
Learn to spot arguments in ordinary language, identify premise and conclusion markers, reconstruct arguments in standard form, add suppressed premises, and test validity and soundness.
Follow oil and gas from exploration to retail: production, refining and transport, plus well costs, seasonal price swings, and how reserves shape company viability.
Inside every pile of data is a vital metric: distinguish cash flow, profitability and web marketing metrics from mere data, compare analyst roles, and score companies on big-data culture.
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