Disclaimer: If you sign up for a (paid) course using this link, R-exercises earns a commission. It does not impact what you pay for a course, and helps us to keep R-exercises free.Course Description
Do you want to step into the ever-growing field of data science? Do you wish to equip yourself with one of the most widely used language for data science?
Packt’s Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it.
Data is on the rise and it’s the need of the hour to process it and make sense out it. Analysts and statisticians need to get this job done. It’s an art to tactfully and efficiently process data. But, as it goes an art becomes a reality only with the help of right tools and the knowledge of using these right. So, it is with data science. R is a powerful language that provides with all the tools required to build probabilistic models, perform data science, and build machine learning algorithms.
With this Learning Path, you’ll be introduced to R Studio and the basics of R. Then, you’ll taken through a number of topics such as handling dates with the lubridate package, handling strings with the stringr package, and making statistical inferences. Finally, the focus will be on machine learning concepts in depth and applying them in the real world with R.
The goal of this course to introduce you to R and have a solid knowledge of machine learning and the R language itself. You’ll also solve numerous coding challenges throughout the course.
This Learning Path is authored by one of the best in the fields.
Selva Prabhakaran Selva Prabhakaran is a data scientist with a large E-commerce organization. In his 7 years of experience in data science, he has tackled complex real-world data science problems and delivered production-grade solutions for top multinational companies. Selva lives in Bangalore with his wife.
What are the requirements?
- This is for absolute beginners. No prior knowledge of R is required.
What am I going to get from this course?
- Create and master the manipulation of vectors, lists, dataframes, and matrices
- Write conditional control structures, and debug and handle errors for efficient error handling
- Handle dates using lubridate and manipulate strings with stringr package
- Work with databases without having to write SQL using the dplyr package
- Work on a full-scale data analysis / data munging project
- Perform pre-model-building steps
- Understand the working behind core machine learning algorithms
- Implement unsupervised learning algorithms
- Construct nice looking charts with Ggplot2
- Build R packages from scratch and submit them to CRAN
Who is the target audience?
- If you are looking to start your data science career, or are already familiar with data science, statistics, and machine learning concepts, but want to switch to R, this Video Learning Path will be a great place to start.
- The Learning Path follows a pragmatic approach where you’ll find step-by-step instructions of the functions, tools, and concepts, and the reason you’re learning about them. Most of the videos close with coding challenges, putting your newly learned skills into practical use immediately. You’ll get hands-on working sessions and detailed explanations.