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Coursera - Data Science Specialization

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Part 1: Integrating R with Web Applications : Business Intelligence, Analytics & Excel *** UPDATE: On 1/23/2015 Surprise! Microsoft announced the acquisition of Revolution Analytics. This is great news and as a result I will be adding that solution option into this mix along with Azure ML R Web Service. *** In this multiple part series, I will share my journey reviewing and developing web applications with the analytics mega-star language R. Why would anyone want to integrate R into a web application or a dashboard? Reviewing R Web Libraries and Frameworks Delivering R in web apps is not a bleeding edge topic. Shiny for R Shiny is a platform as a service (PaaS) for hosting R web applications. After creating my trial account, I was able to easily download the Shiny developer libraries into my free R Studio desktop for authoring and publishing. Now you could also easily display the hosted app page in an HTML iframe or HTML web page viewer control. OpenCPU HTTP API for R During my evaluations, I ended up really liking OpenCPU’s R web framework.

Data Science Bootcamp - 12 week career prep | Metis New York City in-person instruction + ongoing career coaching + job placement support Winter Bootcamp: January 12, 2015 - April 3, 2015 Application Period Closed Spring bootcamp: April 6, 2015 - June 26, 2015 Early Application Deadline*: Monday, February 16 Final Application Deadline: Monday, March 9 Summer bootcamp: June 29, 2015 - September 18, 2015 Early Application Deadline*: Monday, May 11 Final Application Deadline: Monday, June 1 Contact UsApply Now The Bootcamp Experience Instructor and curriculum co-developer Irmak Sirer explores the qualities of a great data scientist, who should apply to the Metis Data Science Bootcamp, and more. The bootcamp experience is intense, but we aim to maximize learning while preventing burn-out. Online Pre-Work We’ll provide a Command Line Crash Course, tutorials to become familiar with Python, and a number of package installation tutorials (i.e., numpy, scipy, pandas, scikit.learn), as well as some preliminary statistics work. Project 1 (codename Benson)

JHU Data Science: More is More Today Jeff Leek, Brian Caffo, and I are launching 3 new courses on Coursera as part of the Johns Hopkins Data Science Specialization. These courses are I'm particularly excited about Reproducible Research, not just because I'm teaching it, but because I think it's essentially the first of its kind being offered in a massive open format. Given the rich discussions about reproducibility that have occurred over the past few years, I'm happy to finally be able to offer this course for free to a large audience. These courses are launching in addition to the first 3 courses in the sequence: The Data Scientist's Toolbox, R Programming, and Getting and Cleaning Data, which are also running this month in case you missed your chance in April. All told we have 6 of the 9 courses in the Specialization available as of today. Every course will be available every month, so don't worry about missing a session.

» ACRL TechConnect Blog Editor’s Note: This post is part of ACRL TechConnect’s series by our regular and guest authors about The Setup of our work. After being tagged by Eric Phetteplace, I was pleased to discover that I had been invited to take part in the “This is How I Work” series. I love seeing how other people view work and office life, so I’m happy to see this trend make it to the library world. Name: Bryan J. Location: Tallahassee, Florida, United States Current Gig: Web Developer, Technology and Digital Scholarship, Florida State University Libraries Current Mobile Device: Samsung Galaxy Note 3 w/ OtterBox Defender cover (just like Becky Yoose!). Current Computer: 15 inch MacBook Pro w/ 8GB of RAM. Current Tablet: 3rd gen. iPad, but I don’t use it much these days. One word that best describes how you work: Structured. What apps/software/tools can’t you live without? Unixy stuff: Other: Dropbox: Keeping my stuff in order across machines is a godsend. What’s your workspace like? What are you currently reading?

Animal Behaviour and Welfare About the Course Animals occupy a huge part of the planet and our lives, and although we rely on them for all aspects of our own wellbeing - food, draught power, medical advances, clothing, sport as well as pleasure, protection and comfort - often their quality of life is questionable. Appreciating how animal's experience the world they live in and the different behavioural needs of the various species we interact with, enables us to gain a better understanding of their welfare requirements, so that long term improvements to animal lives can be made. There are now more than 60 billion land animals raised for meat each year around the world, and with increasing human populations and a rise in meat consumption in many parts of the world, these figures are set to double by 2050. Added to this is a huge and growing world population of dogs and cats, many of whom are strays with associated health and welfare issues. Verified Certificates: Link Coursework to Your Identity Course Syllabus

SAP Design Studio Archives - Visual BI Solutions CSS Tips & Tricks: Sliding Panel Transition in SAP Design Studio Introduction A sliding panel transition can be a really good solution for someone looking to save on dashboard real estate. Sliding it in and out of view with butter-smooth transitions on demand presents a very compelling case when it comes to dashboard aesthetics... Bookmarks in SAP BusinessObjects Design Studio 1.4: Tried and Tested Bookmarks in SAP BusinessObjects Design Studio 1.4 have undergone some enhancements and here are some of my findings after some extensive testing of the bookmark feature on local mode and on the BusinessObjects Platform. Basic Bookmarking: Changes made to the... SAP Design Studio 1.4 – What’s New in APIs SAP Design Studio 1.4 has been very surprising in many interesting ways ever since its release. Fun with CSS in SAP Design Studio! It is always a lot of fun playing around with CSS (Cascading Style Sheets) ! Real-Time and Near Real-Time Streaming using SAP ESP, SAP HANA and SAP Design Studio

All about the position: Data scientist Teradata Aster is seeking experienced individuals with demonstrated capability in the applied analytic and/or data science space. Proficiency in data manipulation, analytic algorithms, advanced math, and/or statistical modeling is required and application development experience a plus. We are looking for exceptional individuals to join our Professional Services team as an Analytic Data Scientists. This client-facing role will be engaged in the design and deployment of solutions. The key requirement is demonstrated capability in applied analytics, with MapReduce and database experience being preferred. “Big Data” analytics is happening right now at Teradata Aster. Develop expertise in areas outside of core comfort zone. - You will learn to - Utilize the Aster technology, combining MPP database and SQL MR functionality, to deliver innovative analytic solutions to our customers. Qualifications - Prior consulting experience | putting the rarin back in librarian since 1999 Questionnaire Design for Social Surveys About the Course This online course is called “Questionnaire Design for Social Surveys” and is based on a course created as part of the Joint Program in Survey Methodology and the Michigan Program in Survey Methodology at ISR. The original course - a core course in our MS program - is one of our most popular courses. It is offered every semester, and in every semester the course is over enrolled. Students with backgrounds in Journalism, Public Health, Criminology, Marketing, Communication, Sociology, Psychology, and Political Science are part of our regular audience. Why does the course have such broad appeal? But designing questions that get good answers is harder than it looks. The target audiences for this course are students and professionals from all fields of social science that are involved in primary data collection. Course Syllabus Click here to view the course syllabus. Recommended Background Course Format

Ataccama - DQ Analyzer Easy, powerful data profiling and analysis + Download DQA Product SheetA critical task for today’s businesses of every size is identifying data issues before they become business issues. DQ Analyzer (DQA) combines advanced data profiling and analysis capabilities with a point-and-click interface that is simple enough for business managers to use without extensive training. DQA may be simple, but it is not simplistic. Best of all, DQA is part of our complete family of products. Download a completely FREE copy of DQA from this website. Features of DQA Speed. DQA Benefits Start fast Using DQ Analyzer is easy and convenient for beginners and seasoned data gurus alike. Work fast DQ Analyzer allows you to profile millions of records in a matter of minutes without the need to consume database processing time. Use regexp, business rules and rich expression language If you know what these terms mean, you know how powerful they are. Work smart Take the first step towards fixing the problems

stat545-ubc.github St. John's University - MySJU News | Events | Webmail | Directory Enter your Username and Password Forgot password? Help FAQs Request Support Copyright for Educators & Librarians Will I get a Statement of Accomplishment after completing this class? Yes. Students who successfully complete the class will receive a Statement of Accomplishment signed by the instructor. What resources will I need for this class? For this course, all you need is an Internet connection and the time to read, write, discuss, and think about our topic. Is this course only for Americans? Throughout the class we will be discussing the copyright law of the United States, and applying that law to the examples we discuss. What is the coolest thing I'll learn if I take this class? Our goal is to help you become a copyright maven, and the coolest thing you will get from this class, we hope, is confidence to do your jobs without undue fear about copyright. For example, is it copyright infringement to decorate a library floor with the complete text from published books? Can I get professional credit for this class? You can get a Statement of Accomplishment that will be signed by the instructors.

10 things statistics taught us about big data analysis In my previous post I pointed out a major problem with big data is that applied statistics have been left out. But many cool ideas in applied statistics are really relevant for big data analysis. So I thought I'd try to answer the second question in my previous post: "When thinking about the big data era, what are some statistical ideas we've already figured out?" If the goal is prediction accuracy, average many prediction models together. There is a similar temptation in big data to get fixated on a tool (hadoop, pig, hive, nosql databases, distributed computing, gpgpu, etc.) and ignore the problem of can we infer x relates to y or that x predicts y.