Data Science and Data Analytics skills are in high demand and R is the programming language of choice for many data professionals. This Applied Data Science with R program emphasizes a hands-on approach to developing job-ready skills for analyzing and visualizing data using R.
You will start the program by learning the fundamentals of R language, including common data types and structures, and utilize it for basic programming and data manipulation tasks.
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Data Science and Data Analytics skills are in high demand and R is the programming language of choice for many data professionals. This Applied Data Science with R program emphasizes a hands-on approach to developing job-ready skills for analyzing and visualizing data using R.
You will start the program by learning the fundamentals of R language, including common data types and structures, and utilize it for basic programming and data manipulation tasks.
Data Science and Data Analytics skills are in high demand and R is the programming language of choice for many data professionals. This Applied Data Science with R program emphasizes a hands-on approach to developing job-ready skills for analyzing and visualizing data using R.
You will start the program by learning the fundamentals of R language, including common data types and structures, and utilize it for basic programming and data manipulation tasks.
As you progress in the program, you will learn about relational database concepts and gain a foundational knowledge of the SQL language. You will access and analyze data in databases using R and SQL through Jupyter notebooks.
You will learn various data analysis techniques – from cleaning and refining data to developing, evaluating, and tuning , data science models. You will also learn how to tell a compelling story with data by creating graphs, visualizations, dashboards and interactive data applications.
In each course you will complete hands-on labs and projects to help you gain practical experience with data manipulation, analysis and visualization using a variety of datasets. You will work with tools like R Studio, Jupyter Notebooks, Watson Studio and related R libraries for data science, including dplyr, Tidyverse, Tidymodels, R Shiny, ggplot2, Leaflet, and rvest.
By the end of the program you will be able to apply the data science skills and techniques that you have accumulated and show case those skills in the R Data Science Capstone Project. involving a real-world dataset, and inspired by a real business challenge. This project will culminate in a presentation for reporting the results of data analysis with stakeholders.
What you'll learn
- Perform basic R programming tasks such as using common data structures, data manipulation, using APIs, webscraping, and working with R Studio and Jupyter.
- Create relational databases and query the data using SQL and R from JupyterLab.
- Complete the data analysis process, including data preparation, statistical analysis, and predictive modeling.
- Communicate data findings using data visualization charts, plots, and dashboards using libraries such as ggplot, leaflet and R Shiny.
- Demonstrate data analysis and visualization skills by completing a project that requires data collection, analysis, basic hypothesis testing, visualization, and modelling performed on real-world datasets.
What's inside
Five courses
SQL for Data Science with R
(15 hours)
SQL for Data Science with R
(15 hours)
Analyzing Data with R
(15 hours)
Analyzing Data with R
(15 hours)
Visualizing Data with R
(6 hours)
Visualizing Data with R
(6 hours)
R Data Science Capstone Project
(6 hours)
R Data Science Capstone Project
(6 hours)
R Programming Basics for Data Science
(7 hours)
R Programming Basics for Data Science
(7 hours)Featured in The Course Notes
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