R Programming – Advanced Analytics In R For Data Science by Kirill Eremenko

This course teaches advanced analytics techniques in R, focusing on essential skills for data science professionals. Participants will learn to manipulate data effectively, handle missing values, and optimize data processing using R’s powerful functions.

Key Skills You Will Acquire

• data preparation techniques: Master essential methods for preparing your datasets, including handling missing records through Median Imputation and Factual Analysis, ensuring your data is ready for analysis.
• data manipulation functions: Learn to utilize important R functions like which() for identifying elements and methods for resetting dataframe indices, enhancing your data handling capabilities.
• string replacement methods: Gain proficiency in string manipulation using gsub() and sub(), allowing you to efficiently clean and format your data for better analysis outcomes.
• date-time manipulation skills: Understand how to convert date-times into POSIXct format, enabling you to work with time series data effectively and accurately in your analyses.

By completing this course, you will be equipped with practical skills that will enhance your data science capabilities, making you a more effective analyst in the field.

Who This Course Is For

• Data analysts seeking to improve their R programming skills for advanced data manipulation and analysis.
• Professionals in data science looking to deepen their understanding of R functions and data preparation techniques.
• Students pursuing careers in analytics who want to master practical applications of R for real-world data challenges.

File Details
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Total Size: 1.3GB

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