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Updated in [April 29th, 2023]

This course, Reading Data into R with readr, provides an overview of the readr package developed by Hadley Wickham. Participants will learn how to import and export data sets, as well as more advanced topics such as type conversion. By the end of the course, participants will have a better understanding of how to use readr to read data into R.

[Applications]
The application of this course can be seen in the ability to read data into R with readr. This course provides a comprehensive overview of the readr package, which can be used to read data from a variety of sources, including text files, databases, and web services. Additionally, the course covers topics such as type conversion, which can be used to ensure that data is in the correct format for analysis. With the knowledge gained from this course, users can confidently read data into R with readr and use it for data analysis.

[Career Paths]
Career Paths:
1. Data Scientist: Data Scientists use readr to read data into R and analyze it to gain insights and make predictions. They use their knowledge of statistics, machine learning, and programming to develop models and algorithms that can be used to solve complex problems. Data Scientists are in high demand and the field is expected to continue to grow in the coming years.

2. Data Analyst: Data Analysts use readr to read data into R and analyze it to gain insights and make decisions. They use their knowledge of statistics, data visualization, and programming to develop reports and dashboards that can be used to inform business decisions. Data Analysts are in high demand and the field is expected to continue to grow in the coming years.

3. Data Engineer: Data Engineers use readr to read data into R and process it for use in applications. They use their knowledge of databases, data warehousing, and programming to develop pipelines and systems that can be used to store and process data. Data Engineers are in high demand and the field is expected to continue to grow in the coming years.

4. Business Intelligence Developer: Business Intelligence Developers use readr to read data into R and create reports and dashboards. They use their knowledge of databases, data warehousing, and programming to develop systems that can be used to store and process data. Business Intelligence Developers are in high demand and the field is expected to continue to grow in the coming years.

[Education Paths]
Recommended Degree Paths:

1. Data Science: Data Science is a rapidly growing field that combines mathematics, statistics, computer science, and domain expertise to extract insights from data. It involves the use of algorithms, methods, and tools to analyze and interpret data. With the increasing availability of data, the demand for data scientists is growing. This degree path will provide learners with the skills and knowledge needed to become a successful data scientist, including the use of readr to read data into R.

2. Computer Science: Computer Science is a field of study that focuses on the design, development, and implementation of computer systems and software. It involves the use of algorithms, programming languages, and data structures to solve problems. This degree path will provide learners with the skills and knowledge needed to become a successful computer scientist, including the use of readr to read data into R.

3. Statistics: Statistics is a field of study that focuses on the collection, analysis, and interpretation of data. It involves the use of mathematical models and techniques to draw conclusions from data. This degree path will provide learners with the skills and knowledge needed to become a successful statistician, including the use of readr to read data into R.

4. Data Analytics: Data Analytics is a field of study that focuses on the analysis of data to gain insights and make decisions. It involves the use of data mining, machine learning, and predictive analytics to uncover patterns and trends in data. This degree path will provide learners with the skills and knowledge needed to become a successful data analyst, including the use of readr to read data into R.