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Matthew Renze
Data science is the practice of transforming data into knowledge, and R is one of the most popular programming language used by data scientists. In a data-driven economy, this combination of skills is in extremely high demand, commanding significant increases in salary, as it is revolutionizing the world. In this course, Data Science with R, you'll learn first learn about the practice of data science, the R programming language, and how they can be used to transform data into actionable insight. Next, you'll learn how to transform and clean your data, create and interpret descriptive statistics, data visualizations, and statistical...
Read more
Data science is the practice of transforming data into knowledge, and R is one of the most popular programming language used by data scientists. In a data-driven economy, this combination of skills is in extremely high demand, commanding significant increases in salary, as it is revolutionizing the world. In this course, Data Science with R, you'll learn first learn about the practice of data science, the R programming language, and how they can be used to transform data into actionable insight. Next, you'll learn how to transform and clean your data, create and interpret descriptive statistics, data visualizations, and statistical...
Read more
Data science is the practice of transforming data into knowledge, and R is one of the most popular programming language used by data scientists. In a data-driven economy, this combination of skills is in extremely high demand, commanding significant increases in salary, as it is revolutionizing the world. In this course, Data Science with R, you'll learn first learn about the practice of data science, the R programming language, and how they can be used to transform data into actionable insight. Next, you'll learn how to transform and clean your data, create and interpret descriptive statistics, data visualizations, and statistical models. Finally, you'll learn how to handle Big Data, make predictions using machine learning algorithms, and deploy R to production. By the end of this course, you'll have the skills necessary to use R and the principles of data science to transform your data into actionable insight.
Register for this course and see more details by visiting:
OpenCourser.com/course/x11gr7/data
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Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Provides a robust foundation for individuals seeking to transition into data science
Emphasizes the practical applications of data science and R programming in real-world scenarios
Taught by Matthew Renze, an experienced instructor in data science and R programming
Requires prior knowledge of programming and data analysis concepts
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Data Science with R.
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Career center
Learners who complete Data Science with R will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists are responsible for collecting, cleaning, and analyzing data to extract meaningful insights. They use their knowledge of statistics, programming, and machine learning to build models that can predict future outcomes. The Data Science with R course provides a solid foundation in the skills and techniques that Data Scientists need to be successful. Students will learn how to use R to transform data into actionable insights, create and interpret descriptive statistics and data visualizations, and build statistical models. They will also learn how to handle Big Data and make predictions using machine learning algorithms.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns. They use their findings to make recommendations to businesses on how to improve their operations. The Data Science with R course provides Data Analysts with the skills they need to be successful. Students will learn how to use R to transform data into actionable insights, create and interpret descriptive statistics and data visualizations, and build statistical models. They will also learn how to handle Big Data and make predictions using machine learning algorithms.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models. They use their knowledge of statistics, programming, and machine learning to build models that can learn from data and make predictions. The Data Science with R course provides Machine Learning Engineers with the skills they need to be successful. Students will learn how to use R to build and deploy machine learning models. They will also learn how to handle Big Data and make predictions using machine learning algorithms.
Statistician
Statistician
Statisticians collect, analyze, interpret, and present data. They use their knowledge of statistics to draw conclusions about the world around them. The Data Science with R course provides Statisticians with the skills they need to be successful. Students will learn how to use R to perform statistical analysis and create data visualizations. They will also learn how to handle Big Data and make predictions using machine learning algorithms.
Business Analyst
Business Analyst
Business Analysts use data to help businesses make better decisions. They collect, clean, and analyze data to identify trends and patterns. They then use their findings to make recommendations to businesses on how to improve their operations. The Data Science with R course provides Business Analysts with the skills they need to be successful. Students will learn how to use R to transform data into actionable insights, create and interpret descriptive statistics and data visualizations, and build statistical models.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data pipelines. They use their knowledge of data management and programming to ensure that data is clean, accurate, and accessible. The Data Science with R course provides Data Engineers with the skills they need to be successful. Students will learn how to use R to transform data into actionable insights, create and interpret descriptive statistics and data visualizations, and build statistical models.
Research Analyst
Research Analyst
Research Analysts collect, analyze, and interpret data to identify trends and patterns. They use their findings to make recommendations to businesses, governments, and other organizations. The Data Science with R course provides Research Analysts with the skills they need to be successful. Students will learn how to use R to transform data into actionable insights, create and interpret descriptive statistics and data visualizations, and build statistical models.
Financial Analyst
Financial Analyst
Financial Analysts use data to help businesses make investment decisions. They collect, clean, and analyze data to identify trends and patterns. They then use their findings to make recommendations to businesses on how to invest their money. The Data Science with R course may be helpful to Financial Analysts. Students will learn how to use R to perform statistical analysis and create data visualizations.
Marketing Analyst
Marketing Analyst
Marketing Analysts use data to help businesses make marketing decisions. They collect, clean, and analyze data to identify trends and patterns. They then use their findings to make recommendations to businesses on how to market their products and services. The Data Science with R course may be helpful to Marketing Analysts. Students will learn how to use R to perform statistical analysis and create data visualizations.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use data to help businesses make decisions about how to improve their operations. They collect, clean, and analyze data to identify trends and patterns. They then use their findings to make recommendations to businesses on how to improve their efficiency and productivity. The Data Science with R course may be helpful to Operations Research Analysts. Students will learn how to use R to perform statistical analysis and create data visualizations.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They use their knowledge of programming languages and software development tools to create software that meets the needs of users. The Data Science with R course may be helpful to Software Engineers. Students will learn how to use R to develop software applications that can handle and analyze data.
Computer Scientist
Computer Scientist
Computer Scientists design, develop, and analyze algorithms and data structures. They use their knowledge of mathematics and computer science to create software that solves problems and meets the needs of users. The Data Science with R course may be helpful to Computer Scientists. Students will learn how to use R to develop software applications that can handle and analyze data.
Data Architect
Data Architect
Data Architects design and implement data management systems. They use their knowledge of data management and programming to create systems that can store, manage, and analyze data. The Data Science with R course may be helpful to Data Architects. Students will learn how to use R to develop data management systems that can handle and analyze data.
Database Administrator
Database Administrator
Database Administrators manage and maintain databases. They use their knowledge of database management systems and programming to ensure that databases are running smoothly and efficiently. The Data Science with R course may be helpful to Database Administrators. Students will learn how to use R to develop database management systems that can handle and analyze data.
Systems Analyst
Systems Analyst
Systems Analysts design and implement computer systems. They use their knowledge of systems analysis and programming to create systems that meet the needs of users. The Data Science with R course may be helpful to Systems Analysts. Students will learn how to use R to develop computer systems that can handle and analyze data.
For more career information including salaries, visit:
OpenCourser.com/course/x11gr7/data
Reading list
We've selected nine books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Data Science with R.
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Serves as the authoritative reference on deep learning, covering its theoretical underpinnings, algorithms, and applications.
Covers advanced statistical learning topics, such as support vector machines, boosting, and bagging, providing a deep understanding of machine learning algorithms.
Provides a comprehensive overview of statistical learning methods, including supervised and unsupervised learning, model selection, and evaluation.
Save
Offers a practical guide to using R for data science tasks, covering data manipulation, visualization, and statistical modeling.
Provides a solid foundation in statistical inference concepts and their application to data science problems.
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Serves as a comprehensive resource for creating dynamic and interactive reports, presentations, and websites with R Markdown.
Guides learners through best practices for reproducible research using R and RStudio, ensuring transparency and integrity in data analysis and reporting.
Provides a comprehensive introduction to machine learning algorithms and their implementation in R.
Introduces deep learning concepts and their implementation using R, covering neural networks, convolutional neural networks, and recurrent neural networks.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/x11gr7/data
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Time
2 hours
Via
Pluralsight
Instructor
Matthew Renze
Good to know
Provides a robust foundation for individuals seeking to transition into data science
Emphasizes the practical applications of data science and R programming in real-world scenarios
Taught by Matthew Renze, an experienced instructor in data science and R programming
Requires prior knowledge of programming and data analysis concepts
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