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<big> '''Modeling and Identifying Neural Systems''' </big>
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<big>'''Sean G. Carver, Ph. D.'''</big>, Data Scientist
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:Data scientist, gifted in the creative analysis and presentation of data.  I have skills and experience creating and conveying penetrating insights from data and models.  In a sense, I have been a data scientist for my entire career, although I did not always call myself that.  I have also called myself a modeler.
  
'''Instructor:''' <big> [http://limbs.lcsr.jhu.edu/User:Scarver Sean G. Carver, Ph.D.]</big>, Postdoctoral Fellow, Psychological and Brain Sciences, The Johns Hopkins University.
 
  
'''Semester:''' Spring 2009.
 
  
'''Seventy-five Word Description:''' This course introduces the paradigms of computational neuroscience and develops skills for modeling neurons and networks of neuronsThe course teaches recent developments in neural system identification -- providing systematic tools for building models of neurons and networks based on experimental data.  Student's final projects will include original research testing these methods on simulated data.
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*<big> [[Doctor Data Professor|'''Mentoring and Tutoring available for the 2023-2024 school year (click here)''']] </big>
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::''I tutor most STEM fields and mentor data projects that send students to the next level---college, graduate school, or a spectacular careerI have a particular interest and experience in baseball analytics to prepare students to work or study as sports data analystsRegardless of your field of interest, I can help you design and implement a project or projects that will get you noticed by employers and university admission committees.''
  
'''Background:''' Neural modeling is often pursued in an ad hoc way.  Researchers add the mechanisms they know about, but need to wave their hands about the ones they don't.  They necessarily make many simplifying assumptions but often include many details that are not needed to parsimoniously capture the phenomena.  [[Background|'''More...''']]
 
  
'''Course Mechanics:''' This class will be a hands on experience.  Pending approval, class will meet twice a week in the Kreiger computer classroom.  Each meeting will last about 1.5 hours.  In addition, there will be three hours per week of supervised computer laboratory time.  Attendence during the laboratory time will be optional.  The purpose of the laboratory time is to allow students, if they choose, to complete computer assignments with the help of the instructor.  An effort will be made to design the weekly homework sets to allow most students to complete most of the homework during the laboratory time.  Grading will be determined 50% by weekly homework and 50% by final projects.  Presently, I am not planning exams.
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* [[Sean G. Carver's Current Research and Data Science Projects|'''Current Research and Data Science Projects''']]
  
Textbook, prerequisites and syllabus to be finalized soon.
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::''Baseball Research Showcase for Undergraduates:''  http://baseball.seancarver.org/novelty.html
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* [https://medium.com/@SeanCarverData '''Blog''']
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* [https://github.com/seancarverphd '''GitHub Repo''']
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* [[Sean G. Carver's Teaching and Course Development|'''Teaching and Course Development''']]
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::''In Spring 2017, I taught Stat 370, [[Syllabus:_Stat_370_Spring_2017|''Introduction to Statistical Computing and Modeling'']].
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::''In Spring 2009, I developed and taught at Johns Hopkins: [[ID_Course_Johns_Hopkins_Spring_2009|Modeling and Identifying Neurosystems]].''
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* [[Sean G. Carver's Biography|'''Biography''']]
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::''I received my Ph.D. in Applied Mathematics from Cornell University in 2003.  I later worked for the University of Maryland, Johns Hopkins University, Yale University, and Data Machines Corp.''
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* [[Sean G. Carver's Textbook Collaborative Authoring|'''Textbook Collaborative Authoring''']]
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::''I wrote: [[Media:The_Data_Professors_Guide_to_Basic_Statistics.pdf|The Data Professor's Guide to Basic Statistics]].
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* [[Sean G. Carver's Publications|'''Publications''']]
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* [https://www.linkedin.com/in/sean-c-a3181331/ '''LinkedIn Profile''']

Latest revision as of 18:31, 11 November 2023

Sean G. Carver, Ph. D., Data Scientist

Data scientist, gifted in the creative analysis and presentation of data. I have skills and experience creating and conveying penetrating insights from data and models. In a sense, I have been a data scientist for my entire career, although I did not always call myself that. I have also called myself a modeler.


I tutor most STEM fields and mentor data projects that send students to the next level---college, graduate school, or a spectacular career. I have a particular interest and experience in baseball analytics to prepare students to work or study as sports data analysts. Regardless of your field of interest, I can help you design and implement a project or projects that will get you noticed by employers and university admission committees.


Baseball Research Showcase for Undergraduates: http://baseball.seancarver.org/novelty.html
In Spring 2017, I taught Stat 370, Introduction to Statistical Computing and Modeling.
In Spring 2009, I developed and taught at Johns Hopkins: Modeling and Identifying Neurosystems.
I received my Ph.D. in Applied Mathematics from Cornell University in 2003. I later worked for the University of Maryland, Johns Hopkins University, Yale University, and Data Machines Corp.
I wrote: The Data Professor's Guide to Basic Statistics.