HarvardX Data Science Professional Certificate. Learn Python for Data Science Online. Online Data Analyst Course. Data Science for Beginners: Hands-On Data Science in Python. Data Science, Machine Learning and Artificial Intelligence are the most demanding skills in today's world, Almost every Multi-National company is working on these new technologies With this Mega Course you will learn all the required tools for Data Science from the very beginning !
Microsoft Professional Program Certificate in Data Science. Analyzing and Visualizing Data with Power BI. 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. 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. MIT Big Data and Social Analytics Certificate Course. 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? Quora.
A Practical Intro to Data Science — Zipfian Academy - Data Science Bootcamp. Are you a interested in taking a course with us?
Learn more on our programs page or contact us. There are plenty of articles and discussions on the web about what data science is, what qualities define a data scientist, how to nurture them, and how you should position yourself to be a competitive applicant. There are far fewer resources out there about the steps to take in order to obtain the skills necessary to practice this elusive discipline. Here we will provide a collection of freely accessible materials and content to jumpstart your understanding of the theory and tools of Data Science. At Zipfian Academy, we believe that everyone learns at different paces and in different ways.
Quora. The Analytics Edge. In the last decade, the amount of data available to organizations has reached unprecedented levels.
Data Analysis and Statistical Inference. Jtleek/datasharing. 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 both for keeping track of programming projects, papers, talks, and data analyses. 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.” Stat545-ubc.github. Data Science Specialization. Welcome · Advanced R. 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. Big Data University. Big Data University. Swirl: Learn R, in R. Data Science Bootcamp - 12 week career prep. 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.
Specialization. Specialization.