stat545-ubc.github git/github guide All statistical/computational scientists should use git and github, but it can be hard to get started. I hope these pages help. (More blather below.) There are many resources for git and github; my aim is to provide the minimal guide to get started. I love git and github. I use git mostly from the command line on a Mac. I would like all of my statistical/computational collaborators to use git and github, so that we may collaborate more easily. Saunak Sen got me started with version control (using subversion), and Pjotr Prins got me to move from subversion to git, but don’t hold either responsible for any errors in my understanding. If you have suggestions for changes or improvements, submit an issue or fork the repo: Follow the instructions above, “Contribute to someone’s repository.” Also see my tutorials on GNU make, knitr, R packages, making a web site with GitHub Pages, data organization, and reproducible research.
jtleek/datasharing 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. “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
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)
The Analytics Edge In the last decade, the amount of data available to organizations has reached unprecedented levels. Data is transforming business, social interactions, and the future of our society. In this course, you will learn how to use data and analytics to give an edge to your career and your life. The class will consist of lecture videos, which are broken into small pieces, usually between 4 and 8 minutes each. What do I need to know about the topic prior to enrolling in the course? You only need to know basic mathematics. What software will be used in the course? We’ll be using two software programs in this class: R and LibreOffice.
quora A Practical Intro to Data Science — Zipfian Academy - Data Science Bootcamp A successful business has always relied on data for making important decisions. It involves talking with the customers face to face or taking a survey via any mean of communication or talking to the customer in person. The data that is collected manually for the businesses to understand the market better. This information is crucial to determine financial costs, time, difficulty level and mother other. Data helps you make better decisions Any business with a website, social media presence, source of electronic money, etc. has some kind of data about their customers, user experience and web traffic. Data helps you solve problems If you are noticing slow sales month or any failed marketing campaign data helps you find out the problem or the reason for the underperformance of your business. Data helps you see your performance Data provides you with all the information about how your team is working by collecting and reviewing the data of their performance of all month. </center? </center?
MIT Big Data and Social Analytics Certificate Course | GetSmarter Imagine what you could learn about humanity, and the way we interact not only with technology, but also each other, given the amount of data available to be analyzed. Social physics - a key focus of this course - is described by Professor Alex Pentland, one of the world’s leading data scientists, as “statistics meets big data to understand people”. It unlocks a whole new way to think about big data analytics by shifting focus to how the results of data analysis not only contribute to better decision making, but also how they can better assist humanity. These analytical findings can lead to more effective marketing, new revenue opportunities, better customer service, improved operational efficiency, competitive advantages over rival organizations as well as a range of other business benefits. Course overview Is this course for you? This course is suitable for technically-minded graduates and working professionals in any role, across any industry.
Artificial Intelligence This is an Archived Course EdX keeps courses open for enrollment after they end to allow learners to explore content and continue learning. All features and materials may not be available, and course content will not be updated. Check back often to see when new course start dates are announced. Artificial intelligence is already all around you, from web search to video games. AI methods plan your driving directions, filter your spam, and focus your cameras on faces. The course will introduce the basic ideas and techniques underlying the design of intelligent computer systems. Statistical and decision–theoretic modeling paradigm. Join us today to learn more about how AI affects your life, and where it is headed in the future.
Specialization Current session: Nov 7 — Dec 12. About the Course Welcome to the Cloud Computing Applications course, the second part of a two-course series designed to give you a comprehensive view on the world of Cloud Computing and Big Data! In this second course we continue Cloud Computing Applications by exploring how the Cloud opens up data analytics of huge volumes of data that are static or streamed at high velocity and represent an enormous variety of information.