Course Report
Find detailed report of this course which helps you make an informed decision on its relevance to your learning needs. Find out the course's popularity among Careervira users and the job roles that would find the course relevant for their upskilling here. You can also find how this course compares against similar courses and much more in the course report.
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Course Features
Duration
4 hours
Delivery Method
Online
Available on
Limited Access
Accessibility
Mobile, Desktop, Laptop
Language
English
Subtitles
English
Level
Intermediate
Teaching Type
Self Paced
Video Content
4 hours
Course Description
Highlights
Hands on training
Top 10 Percentile
Pedagogy
Top 30 Percentile
Rating & Reviews
Top 30 Percentile
Parameters
Pedagogy
Acquire all major R Programming skills in this course for seamless integration into your daily life. Develop a versatile skill set, allowing you to confidently apply what you've learned in various practical scenarios, enhancing your daily experiences and overall proficiency. An exceptional course in R Programming, this stands out for its Self Paced learning approach. Learners have the flexibility to progress at their own speed, tailoring the experience to their individual needs.
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Hands on training
This course stands out as one of the top 10 percentile options in R Programming, offering unparalleled hands-on training. Learners gain practical experience and skills through immersive learning, preparing them for real-world challenges. It ensures a well-rounded skill set, catering to a range of learning preferences. With a focus on Hands on training as well as essential Case Based Learning and Virtual Labs, this course is tailored to meet diverse educational needs.
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Rating & Reviews
This highly acclaimed course is among the top-rated in R Programming, boasting a rating greater than 4 and an overall rating of 5.0. Its exceptional quality sets it apart, making it an excellent choice for individuals seeking top-notch learning experience in R Programming.
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Course Overview
Virtual Labs
International Faculty
Case Based Learning
Post Course Interactions
Case Studies,Hands-On Training,Instructor-Moderated Discussions
Skills You Will Gain
Prerequisites/Requirements
Introduction to Regression in R
What You Will Learn
This course teaches the big ideas in machine learning: how to build and evaluate predictive models, how to tune them for optimal performance, how to preprocess data for better results, and much more
The popular caret R package, which provides a consistent interface to all of R's most powerful machine learning facilities, is used throughout the course
Course Instructors
Zachary Deane-Mayer
VP, Data Science at DataRobot
Max Kuhn
Software Engineer at RStudio and creator of caret
Course Reviews
Average Rating Based on 3 reviews
100%