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Filip Schouwenaars and Jonathan Sanito

R is rapidly becoming the leading language in data science and statistics. Today, R is the tool of choice for data science professionals in every industry and field. Whether you are full-time number cruncher, or just the occasional data analyst, R will suit your needs.

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R is rapidly becoming the leading language in data science and statistics. Today, R is the tool of choice for data science professionals in every industry and field. Whether you are full-time number cruncher, or just the occasional data analyst, R will suit your needs.

This introduction to R programming course will help you master the basics of R. In seven sections, you will cover its basic syntax, making you ready to undertake your own first data analysis using R. Starting from variables and basic operations, you will eventually learn how to handle data structures such as vectors, matrices, data frames and lists. In the final section, you will dive deeper into the graphical capabilities of R, and create your own stunning data visualizations. No prior knowledge in programming or data science is required.

What makes this course unique is that you will continuously practice your newly acquired skills through interactive in-browser coding challenges using the DataCamp platform. Instead of passively watching videos, you will solve real data problems while receiving instant and personalized feedback that guides you to the correct solution.

Enjoy!

edX offers financial assistance for learners who want to earn Verified Certificates but who may not be able to pay the fee. To apply for financial assistance, enroll in the course, then follow this link to complete an application for assistance.

Note: These courses will retire in June. Please enroll only if you are able to finish your coursework in time.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Aids students who want to choose R programming for data science
Provides hands-on practice and continuous assessment to reinforce understanding
Well-structured, with a clear learning path from basic data analysis to advanced visualizations
Developed by experienced instructors in data science
Designed for learners with no prior programming experience

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Reviews summary

R for data science made practical

Introduction to R for Data Science is an engaging, practical course for learners with little to no programming experience who want to add data science to their skillset. Students will appreciate the interactive exercises that provide personalized feedback to help them master the basics of R, data structures, and data visualization. While the course covers foundational concepts well, learners looking for more advanced R programming skills may need to supplement with additional resources.
Engaging exercises with actionable feedback
"The most helpful part to me is the interactive programming exercise."
"This class will give you solid foundations... and it does so very efficiently and very well."
Accessible to beginners with no programming experience
"This course is actually more like half a course, but it does that half extremely well."
"This is a very useful introduction to R."
"No prior knowledge in programming or data science is required."
Covers foundational R concepts but not advanced skills
"Course designed for those who can not program at all."
"But if you have some programming experience I would rather recommend coursera course about R."
"There is no coverage on control flow, functions, or vectorized operations, which is needed for an actual working knowledge of R."

Activities

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Career center

Learners who complete Introduction to R for Data Science will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists are responsible for developing and implementing data-driven solutions to business problems. They use their skills in data analysis, machine learning, and artificial intelligence to build models that can predict future outcomes. This course can help you become a Data Scientist by providing you with the skills you need to collect, clean, and analyze data. You will also learn how to use R, a programming language that is commonly used for data science.
Data Analyst
Data Analysts are responsible for collecting, cleaning, and analyzing data to identify trends and patterns. They use their findings to make recommendations to businesses on how to improve their operations. This course can help you become a Data Analyst by providing you with the skills you need to collect, clean, and analyze data. You will also learn how to use R, a programming language that is commonly used for data analysis.
Statistician
Statisticians are responsible for collecting, analyzing, and interpreting data. They use their findings to make inferences about populations and to develop statistical models. This course can help you become a Statistician by providing you with the skills you need to collect, clean, and analyze data. You will also learn how to use R, a programming language that is commonly used for statistics.
Machine Learning Engineer
Machine Learning Engineers are responsible for developing and deploying machine learning models. They use their skills in data analysis, machine learning, and artificial intelligence to build models that can learn from data and make predictions. This course can help you become a Machine Learning Engineer by providing you with the skills you need to collect, clean, and analyze data. You will also learn how to use R, a programming language that is commonly used for machine learning.
Risk Analyst
Risk Analysts are responsible for identifying and assessing risks to businesses. They use their skills in data analysis, statistics, and financial modeling to develop models that can predict future risks. This course can help you become a Risk Analyst by providing you with the skills you need to collect, clean, and analyze data. You will also learn how to use R, a programming language that is commonly used for risk analysis.
Operations Research Analyst
Operations Research Analysts are responsible for developing and implementing mathematical models to help businesses solve complex operational problems. They use their skills in data analysis, optimization, and simulation to build models that can improve business processes. This course can help you become an Operations Research Analyst by providing you with the skills you need to collect, clean, and analyze data. You will also learn how to use R, a programming language that is commonly used for operations research.
Data Visualization Specialist
Data Visualization Specialists are responsible for creating visual representations of data. They use their skills in data analysis, design, and communication to create visualizations that can help businesses understand their data and make better decisions. This course can help you become a Data Visualization Specialist by providing you with the skills you need to collect, clean, and analyze data. You will also learn how to use R, a programming language that is commonly used for data visualization.
Quantitative Analyst
Quantitative Analysts are responsible for developing and implementing quantitative models to help businesses make investment decisions. They use their skills in data analysis, statistics, and financial modeling to build models that can predict future financial outcomes. This course can help you become a Quantitative Analyst by providing you with the skills you need to collect, clean, and analyze data. You will also learn how to use R, a programming language that is commonly used for quantitative analysis.
Business Analyst
Business Analysts are responsible for analyzing business processes and identifying areas for improvement. They use their skills in data analysis and business process modeling to develop solutions that can help businesses improve their operations. This course can help you become a Business Analyst by providing you with the skills you need to collect, clean, and analyze data. You will also learn how to use R, a programming language that is commonly used for business analysis.
Market Researcher
Market Researchers are responsible for conducting research to understand the needs and wants of consumers. They use their skills in data analysis, survey design, and data visualization to collect and analyze data about consumers. This course can help you become a Market Researcher by providing you with the skills you need to collect, clean, and analyze data. You will also learn how to use R, a programming language that is commonly used for market research.
Software Engineer
Software Engineers are responsible for designing, developing, and maintaining software applications. They use their skills in programming, data structures, and algorithms to build software that meets the needs of businesses. This course can help you become a Software Engineer by providing you with the skills you need to collect, clean, and analyze data. You will also learn how to use R, a programming language that is commonly used for software development.
Database Administrator
Database Administrators are responsible for managing and maintaining databases. They use their skills in data management, database design, and performance tuning to ensure that databases are running smoothly and efficiently. This course can help you become a Database Administrator by providing you with the skills you need to collect, clean, and analyze data. You will also learn how to use R, a programming language that is commonly used for database administration.
Financial Analyst
Financial Analysts are responsible for analyzing financial data and making recommendations to businesses on investment decisions. They use their skills in data analysis, financial modeling, and valuation to develop models that can predict future financial outcomes. This course can help you become a Financial Analyst by providing you with the skills you need to collect, clean, and analyze data. You will also learn how to use R, a programming language that is commonly used for financial analysis.
Product Manager
Product Managers are responsible for developing and launching new products. They use their skills in product development, data analysis, and market research to create products that meet the needs of consumers. This course can help you become a Product Manager by providing you with the skills you need to collect, clean, and analyze data. You will also learn how to use R, a programming language that is commonly used for product management.
Data Engineer
Data Engineers are responsible for building and maintaining the infrastructure that supports data analysis and machine learning. They use their skills in data management, distributed systems, and cloud computing to build systems that can handle large volumes of data. This course can help you become a Data Engineer by providing you with the skills you need to collect, clean, and analyze data. You will also learn how to use R, a programming language that is commonly used for data engineering.

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