Data science is huge, and the ability to tackle analysis problems in a highly specialized and fast language will help people who are not engineers approach the topic.
DurationData science is huge, and the ability to tackle analysis problems in a highly specialized and fast language will help people who are not engineers approach the topic.
Using R, an open-source, dedicated statistical language will appeal to a broad audience from healthcare data analysts to software engineers looking to learn more high level statistical packages
If you want to level-up your analysis skills and learn a new way to process, analyze and visualize data, join us and learn the fundamentals of R.
Since 2011, General Assembly has transformed tens of thousands of careers through pioneering, experiential education in today’s most in-demand skills.
When you learn web development, data, design, business, and more with GA, you get:
Award-winning curriculum and expert instructors, on campus and online.
A global, professional community of 40,000-plus full- and part-time alumni.
Career results from leading-edge courses, with mentorship each step of the way.
In this course, you’ll use advanced modeling techniques to predict, classify and group data. You’ll use more advanced techniques to help you understand both inferential and predictive approaches.
The R Programming Introduction course will help students learn how to perform data analysis with the R language and software environment, even if they have little to no programming experience.
The Certified Financial Analytics Practitioner' (CFAP) course is a focused 32-hour instructor-led training and certification program that equips participants to explore+analyze+solve financial sector problems using popular analytics tools such as R & Advanced Excel.
Accelebrate's Introduction to R Programming training course teaches attendees how to use R programming to explore data from a variety of sources by building inferential models and generating charts, graphs, and other data representations.
Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience.
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