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| Course Fee | 1,150 |
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Total Fees |
1,150 (USD) |
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Inclusions in Koenig's Learning Stack may vary as per policies of OEMs
Koenig Learning Stack
Free Pre-requisite TrainingJoin a free session to assess your readiness for the course. This session will help you understand the course structure and evaluate your current knowledge level to start with confidence.
Assessments (Qubits)Take assessments to measure your progress clearly. Koenig's Qubits assessments identify your strengths and areas for improvement, helping you focus effectively on your learning goals.
Post Training ReportsReceive comprehensive post-training reports summarizing your performance. These reports offer clear feedback and recommendations to help you confidently take the next steps in your learning journey.
Class RecordingsGet access to class recordings anytime. These recordings let you revisit key concepts and ensure you never miss important details, supporting your learning even after class ends.
Free Lab ExtensionsExtend your lab time at no extra cost. With free lab extensions, you get additional practice to sharpen your skills, ensuring thorough understanding and mastery of practical tasks.
Free Revision Classes Join our free revision classes to reinforce your learning. These classes revisit important topics, clarify doubts, and help solidify your understanding for better training outcomes.
Inclusions in Koenig's Learning Stack may vary as per policies of OEMs
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♱ Excluding VAT/GST
You can request classroom training in any city on any date by Requesting More Information
Inclusions in Koenig's Learning Stack may vary as per policies of OEMs
To successfully undertake training in the R Programming course with Koenig Solutions, students should meet the following minimum prerequisites:
Basic understanding of programming concepts: While prior experience in R is not mandatory, familiarity with programming logic and constructs such as variables, loops, and conditional statements will be beneficial.
Fundamental knowledge of statistics: As R is a language designed for statistical analysis, a grasp of basic statistical concepts will help students comprehend the course material more effectively.
Proficiency in working with computers: Students should be comfortable with installing software and managing files and directories on their operating system (Windows, macOS, or Linux).
Willingness to learn and solve problems: R has a steep learning curve, and students should be prepared to engage with new concepts and troubleshoot issues that may arise during the learning process.
Basic mathematical skills: Understanding of high school level mathematics is recommended since the course involves concepts like distributions, hypothesis testing, and regression.
English comprehension: As the course material is presented in English, a good command of the English language is necessary for following the lessons and understanding the course content.
Remember, these are the minimum requirements, and possessing additional skills in these areas will only enhance your learning experience. The R Programming course is designed to be accessible to those with a keen interest in data analysis and a dedication to learning.
Learn R Programming with Koenig Solutions to master data analysis, statistical modeling, and graphical representation for real-world applications.
Target Audience:
This R Programming course equips learners with essential R programming skills, statistical concepts, and data analysis techniques for effective data manipulation and interpretation.
Learning Objectives and Outcomes:
