http://catalog.yale.edu/handbook-instructors-undergraduates-yale-college/grades/reporting/
QT:{{"
Term grades for the spring term are due seven days after the end of final examination period; in 2017–2018, this date is May 16, 2018. In the spring term, grades are due for seniors within forty-eight hours of the end of final examination period; in 2017–2018, this date is May 11, 2018.
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Points of significance – #MachineLearning: supervised methods https://www.Nature.com/articles/nmeth.4551 Nice discussion of the k in k-NN & the slack parm. C, penalizing misclassified points in SVM — both which act somewhat analogously as regularizers. Good for #teaching
Genic Intolerance to Functional Variation & the Interpretation of Personal Genomes
http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1003709 Nice plot of the number of rare v common variants in each gene to find outliers particularly tolerant to impactful (eg #LOF) mutations
http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1003709
Petrovski et al ’13
Webinar Invitation
General Data Science Overview
Date: November 1st
Time: 11:00 a.m. EDT
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How can we effectively and efficiently teach statistical thinking and computation to students with little to no background in either? How can we equip them with the skills and tools for reasoning with various types of data and leave them wanting to learn more?
In this talk we describe an introductory data science course that is our (working) answer to these questions. ….
Webinar Recordings:
We try to record every webinar we host and post all materials on our website. http://www.rstudio.com/resources/webinars/
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http://researchdata.yale.edu/training-calendarthe Research Data Support website has published a unified calendar for data and research skills training provided by the Library, Center for Research Computing, Medical Library, and Center for Teaching and Learning.
The Research Data Consultation Group (http://researchdata.yale.edu/) has considered aggregating data science training information into a unified calendar.
Also, there’s an instruction calendar at the library
(http://csssi.yale.edu/instruction/workshop-and-instruction-calendar)
Naive #Bayes Classification explained with Python code
http://www.DataScienceCentral.com/profiles/blogs/naive-bayes-classification-explained-with-python-code Nice worked example; good for #teaching HT @KirkDBorne
Lifelong Learning
http://www.Economist.com/news/special-report/21714169-technological-change-demands-stronger-and-more-continuous-connections-between-education Future for colleges? Microcredentails & Nanodegrees inspired by albums unbundled into iTunes songs
interesting view of where short “workshops” fit relative to the traditional course
QT:{{”
Scott DeRue, the dean of the Ross School of Business at the University of Michigan, says the unbundling of educational content into smaller components reminds him of another industry: music. Songs used to be bundled into albums before being disaggregated by iTunes and streaming services such as Spotify. In Mr DeRue’s analogy, the degree is the album, the course content that is freely available on MOOCs is the free streaming radio service, and a “microcredential” like the nanodegree or the specialisation is paid-for iTunes.
How should universities respond to that kind of disruption? For his answer, Mr DeRue again draws on the lessons of the music industry. Faced with the disruption caused by the internet, it turned to live concerts, which provided a premium experience that cannot be replicated online. The on-campus degree also needs to mark itself out as a premium experience, he says.
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Cracking the code of when #genetic variants matter, by @CarlZimmer https://www.StatNews.com/2016/08/17/genetic-variants-ex-ac-sequence/ Underscores need for realistic guidelines on risk
