Brief Introduction
You should take this course if you want to cover the state of the art in data modeling and visualization techniques using the R programming language.Course Summary
Learn how to analyze and visualize data using a variety of tools and techniques. This course covers data cleaning and wrangling, exploratory data analysis, data visualization, and more.Key Learning Points
- Learn to use Python and its libraries for data analysis and visualization
- Gain hands-on experience with real-world datasets
- Learn to create visualizations that effectively communicate insights
Related Topics for further study
Learning Outcomes
- Perform data cleaning and wrangling techniques
- Conduct exploratory data analysis to gain insights
- Create effective visualizations to communicate findings
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of Python programming
- Familiarity with data structures and algorithms
Course Difficulty Level
IntermediateCourse Format
- Self-paced
- Online
- Project-based
Similar Courses
- Data Science Essentials
- Data Visualization with Tableau
Related Education Paths
Related Books
Description
This course will introduce students to the field by covering stateÂ-of-Âthe-art modeling, analysis and visualization techniques.Requirements
- Programming experience Mathematics: basic linear algebra, calculus, introductory probability No background in machine learning is required See the Technology Requirements for using Udacity.
Knowledge
- Instructor videosLearn by doing exercisesTaught by industry professionals
Outline
- lesson 1 Programming in R The R Programming Language R Programming Syntax R Programming and Data Structures lesson 2 Data Analysis Data Preprocessing Data Processing Data Visualization lesson 3 Regression Logistic Regression Linear Regression Regularization
Summary of User Reviews
Learn data analysis and visualization techniques with this comprehensive course by Udacity. Students have provided overwhelmingly positive feedback on the content, format and practical applications of the course. Many users appreciated the real-world examples and hands-on projects included in the curriculum.Key Aspect Users Liked About This Course
Real-world examples and hands-on projectsPros from User Reviews
- Clear and concise instructions
- Practical applications and real-world examples
- Interactive projects and quizzes
- In-depth coverage of data visualization tools
Cons from User Reviews
- Some sections may be too basic for advanced learners
- Limited support for technical issues
- No certificate provided with the free version
- Some students found the pacing to be slow
- No feedback provided on projects
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