R Programming Hands-on Specialization for Data Science (Lv1)
An in-depth course on R language with real-world Data Science examples to supercharge your R data analysis skills
4.07 (543 reviews)
21 490
students
11 hours
content
May 2017
last update
$13.99
regular price
What you will learn
Setup and Use Development Environment for R
Install and Use Packages in R
Learn and use Atomic Data Types in R
Learn and apply advanced explicit/Implicit Coercioning in R
Learn multiple approaches to create vectors in R
Understand nuances and implications in Vector Coercions
Understand Vector indexing principles in R
Understand and leverage Vectors' flatness property
Understand Vector Labels and Attributes and their practical use-cases
Learn Matrices and multiple approaches for creation
Learn how Matrices Dimension Property works
Learn advanced techniques for Matrices Indexing
Learn Matrices Operations and Important Functions
Learn the amazing use-cases of Lists
Learn to leverage Lists' Recursive Nature
Learn multiple ways to create Lists (including from other data structures)
Learn critical nuances in Lists Indexing, Labels and Lists Properties
Learn multiple approaches to create Data Frames (including from other data structures)
Learn Data Frames sub-setting (beginner to advanced)
Learn how to impute missing values in Data Frames for efficient Data Analysis
Learn R Control Structures (Conditional statements and loops)
Learn to create and use R Functions
Understand Web Scraping Process
Learn R's Apply family of functions for advanced data manipulation
Learn Multiple ways to perform Web Scraping in R
Learn how to perform Data Munging, Cleansing and Transformation in R
Learn HTML and Document Object Model in the context of Web Scraping
Learn XPath Query Language for Web Scraping
Learn RSelenium setup and usage for advanced Web Scraping
Learn Regular Expression Functions in R for advanced analysis
Learn advanced Data Frames techniques for efficient data analysis
Learn how to perform statistical analysis and visualisation to derive insights in R
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Comidoc Review
Our Verdict
R Programming Hands-on Specialization for Data Science (Lv1) offers aspiring data analysts and machine learning practitioners an extensive look into R programming. Its real-world examples, implementation in both R and Python, and detailed explanations serve as notable strengths, ensuring students a strong foundation in R concepts and their applications. However, inconsistent audio quality, sparse quizzes and scenarios, and some challenges with RSelenium interaction may impact the overall learning experience for some students. The course's potential is most visible for those seeking to grasp R programming fundamentals before exploring more complex techniques as part of further studies or analysis.
What We Liked
- Covers a wide range of topics in R programming, providing a solid foundation for data analytics and machine learning.
- Implementation of concepts in both R and Python offers a comparative understanding and versatility in problem-solving.
- In-depth explanations and intuition videos make the course suitable for learners with different skill levels.
- Real-world examples, real-life applications, and an industrial perspective offered throughout the course.
Potential Drawbacks
- Auto-generated captions may not accurately represent lessons, particularly when lecturer speaks rapidly with an Indian accent.
- Quizzes and scenarios are limited, impacting hands-on engagement and practice.
- Several reviews mention issues with connecting to RSelenium server and interacting within the course.
- Theoretical foundations of certain topics could be more concise in order to allow for deeper dives into advanced techniques.
Related Topics
1055398
udemy ID
30/12/2016
course created date
14/11/2019
course indexed date
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