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1. Data Data Science Science Courses Courses - by Math Academy Tutoring

2. Introduction Introduction A quick overview of the subject Data Science is the study of the datum, which is the Being of a being in its there-being. The datum of a being is its having been measured, and thus observed in one of its states. The science of data is thus how to interrogate data such as to reveal the being that has been measured, and thus the whole from the part that was revealed. The datum expresses the quantification of a quality of an object, whether that is as basic as mere existence or aspects pertaining to other objects. Thus, Data Science concerns itself with the question of the discretized datum of Being, and thus also with its dual, the interpretive continuum of Being. While only a finitude of nature may be measured, the continuum of its being is the question of understanding. The continuum is the hermeneutical or interpretative understanding of being while discretion is the articulation of being – it must first be before it can make itself known by articulation.

3. The Scientific Process: Question- Asking & Temporality 1 The scientific process is the temporality of question- asking, and as such the basis for temporality, which ontologically answers the epistemological questions in terms of genesis or the `coming forth from’ that underlies notions of causality. 2 The Experimental Set-up: Breaking the Flow of Nature Nature is explained by a parameterized model. Each parameter, as a functional aggregation of measurement samples, has itself a corresponding distribution as it occurs in nature along the infinite, universal horizon of measurement. Lessons to Lessons to be Covered be Covered Deriving The Distribution of Normalcy 3 The question with measurement is not, “what is the true distribution of the object in question in nature?”,

4. Part I: The Scientific Process Syllabus Includes : Syllabus Includes : Hypothesis Testing Experimental Setup Part II: Measurement The Lebesque Measure Quantum Theory of the Action of Measurement Part III: Statistical Analysis Summarizing Data via Statistics & Estimators Underlying Distributions Testing Hypotheses Non-Parametric Techniques Part IV: Stochastic Process Adding time to the evolution of a statistic estimation Markov Chains, Limiting Processes, & Stationary Distributions Part V: Dynamic Systems Sensitivity in Measurement and Chaos Theory Part VI: Communication Systems: An Integrative Approach Stochastic Processes are Dynamical Systems A Social & Natural Scientific paradigm of Communicating Systems Data only exists in communication networks

5. Requirements for Class Requirements for Class 2 hrs of Individualized Tutoring Weekly For 12 Weeks Supplementary Group Zoom Lectures Participation in Public Research colloquia

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