Why R is Hard to Learn by Bob Muenchen R has a reputation of being hard to learn. Some of that is due to the fact that it is radically different from other analytics software. Some is an unavoidable byproduct of its extreme power and flexibility. And, as with any software, some is due to design decisions that, in hindsight, could have been better. If you have experience with other analytics tools, you may at first find R very alien. Below is a list of complaints about R that I commonly hear from people taking my R workshops. Unhelpful Help R’s help files are often thorough and usually contain many working examples. Another confusing aspect to R’s help files stems from R’s ability to add new capabilities (called methods) to some functions as you load add-on packages. So an R beginner has to learn much more than a SAS or SPSS beginner before he or she will find the help files very useful. Misleading Function or Parameter Names Another command that commonly confuses beginners is the simple “if” function.
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)
Problems | Locations Rosalind is a platform for learning bioinformatics and programming through problem solving. Take a tour to get the hang of how Rosalind works. If you don't know anything about programming, you can start at the Python Village. For a collection of exercises to accompany Bioinformatics Algorithms book, go to the Textbook Track. Otherwise you can try to storm the Bioinformatics Stronghold right now. If you are completely new to programming, try these initial problems to learn a few basics about the Python programming language. Bioinformatics Stronghold Discover the algorithms underlying a variety of bioinformatics topics: computational mass spectrometry, alignment, dynamic programming, genome assembly, genome rearrangements, phylogeny, probability, string algorithms and others. Ready-to-use software tools abound for bioinformatics analysis. Bioinformatics Textbook Track
Quick-R: Home Page 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
UNIX / Linux Tutorial for Beginners A beginners guide to the Unix and Linux operating system. Eight simple tutorials which cover the basics of UNIX / Linux commands. Introduction to the UNIX Operating System What is UNIX? Files and processes The Directory Structure Starting an UNIX terminal Tutorial One Listing files and directories Making Directories Changing to a different Directory The directories . and .. Recommended UNIX and Linux books If you wish to continue learning Unix, here is a list of good Unix and Linux books, ranging from beginners to advanced. Download This tutorial is available for download so you can work offline.
Code School - Try R stat545-ubc.github NumericAndScientific/Plotting Over the years many different plotting modules and packages have been developed for Python. For most of that time there was no clear favorite package, but recently matplotlib has become the most widely used. Nevertheless, many of the others are still available and may suit your tastes or needs better. Matplotlib is an Open Source plotting library designed to support interactive and publication quality plotting with a syntax familiar to Matlab users.