The R programming language is purpose-built for data analysis. R is the key that opens the door between the problems that you want to solve with data and the answers you need to meet your objectives. This course starts with a question and then walks you through the process of answering it through data. You will first learn important techniques for preparing (or wrangling) your data for analysis. You will then learn how to gain a better understanding of your data through exploratory data analysis, helping you to summarize your data and identify relevant relationships between variables that can lead to insights. Once your data is ready to analyze, you will learn how to develop your model and evaluate and tune its performance. By following this process, you can be sure that your data analysis performs to the standards that you have set, and you can have confidence in the results.
About this Course
What you will learn
Prepare data for analysis by handling missing values, formatting and normalizing data, binning, and turning categorical values into numeric values.
Compare and contrast predictive models using simple linear, multiple linear, and polynomial regression methods.
Examine data using descriptive statistics, data grouping, analysis of variance (ANOVA), and correlation statistics.
Evaluate a model for overfitting and underfitting conditions and tune its performance using regularization and grid search.
Skills you will gain
- Data Science
- Statistical Analysis
- R Programming
- Data Analysis
- Data Visualization (DataViz)
Syllabus - What you will learn from this course
Introduction to Data Analysis with R
Exploratory Data Analysis
Model Development in R
- 5 stars84.15%
- 4 stars9.28%
- 3 stars2.18%
- 2 stars1.63%
- 1 star2.73%
TOP REVIEWS FROM DATA ANALYSIS WITH R
I enjoyed this course! Great Instructors and Teaching Staff. Loved the Syllabus
this course is not for the week, its not challenging but you have to litle dictated...
It is excellent course. I recommend for all that do not have a lot of knowledge and experience in data analysis with R Programming. Thank you for this opportunity.
I could not use WatsonStudio and used RStudio instead. It might have caused problems to the reviewers of peer assignment. Course content is good.
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