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)
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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. “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. Our total compensation approach includes a competitive base salary, 401(k), strong work/family programs, and medical, dental and disability coverage. Qualifications - Prior consulting experience
Normal Distribution Calculator The Normal Distribution Calculator makes it easy to compute cumulative probability, given a normal random variable; and vice versa. For help in using the calculator, read the Frequently-Asked Questions or review the Sample Problems. To learn more about the normal distribution, go to Stat Trek's tutorial on the normal distribution. Note: The normal distribution table, found in the appendix of most statistics texts, is based on the standard normal distribution, which has a mean of 0 and a standard deviation of 1. To produce outputs from a standard normal distribution with this calculator, set the mean equal to 0 and the standard deviation equal to 1. Instructions: To find the answer to a frequently-asked question, simply click on the question. Why is the normal distribution so important? The normal distribution is important because it describes the statistical behavior of many real-world events. What is a standard normal distribution? There are an infinite number of normal distributions.
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