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Dplyr for Data Wrangling
- Learn how to write codes and manipulate data using the Dplyr package in R Programming
Created by Selva Prabhakaran
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10 Video Lessons
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English
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English captions
Validity Period: 365 days
Already Subscribed? Click here to access your courses
- Course Certificate
- Code Walkthroughs
- Practice Data
- Money Back if not satisfied
- Algorithms explanation
- 2h 26m of Self-paced videos
- Downloadable resources
- Q&A sessions with experts
What you will learn
01
Data Manipulation verbs
02
Types of vibes
03
Groupby Function
04
Joins Function
Course Curriculum
4 Modules | 14 Sessions | 38 min Total Time
Overview
Sessions: 3 | Time: 4 min
Pipes
Sessions: 3| Time: 9 min
Data Manipulation Verbs & Summarization
Sessions: 4| Time: 14 min
Joins
Sessions: 4| Time: 11 min
Requirements
- Basic Maths and Logical Reasoning
- Curiosity about Data Science
- Learning Mindset
Who should attend this course?
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Future Data Scientists and ML Engineers
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Product Managers, Program Managers, Scrum Masters working in ML/Data science project
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Software/Data engineers interested in quantitative analysis
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Software engineers interfacing with data science team
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Executives who have to lead or interact with Data Scientists
Instructor
Selva Prabhakaran Principal Data Scientist
My name is Selva, and I am super excited to mentor you on this project!
I head the Data Science team for a global Fortune 500 company and over the last
10 years of my data science experience I’ve deployed 20+ global products. I’m
also the Founder & Chief Author of Machine Learning Plus, which has over 4M
annual readers.
I specialize in covering the in-depth intuition and maths of any concept or
algorithm. And based on my existing student requests, I’ve put up the series of
courses and projects with detailed explanations – just like an on the job
experience. Hope you love it!
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4.5+Instructor rating
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200+ reviews
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10K+students
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15+ Courses
Validity Period: 365 days
Already Subscribed? Click here to access your courses
- Workshop Certificate
- Code Walkthroughs
- Practice Data
- Money Back if not satisfied
- Algorithms explanation
- 2h 26m of Self-paced videos
- Downloadable resources
- Q&A sessions with experts