R programming for Beginners
R programming for Beginners, available at $59.99, has an average rating of 4.81, with 39 lectures, based on 8 reviews, and has 1015 subscribers.
You will learn about Students will learn the fundamentals of R programming Students will learn how to write functions, loops and conditional statements Students will learn data visualisation in R Students will learn Statistics in R Students will learn how to write code in R Students will gain knowledge about R syntax and language This course is ideal for individuals who are Beginners who want to learn R programming language or Beginners who want to learn R syntax or Beginners who want to learn how to write code in R or Beginners who want to learn how to visualise data in R or Beginners who want to learn how to use R for statistics or Beginners who want to learn the building blocks of programming such as loops, functions and conditional statements It is particularly useful for Beginners who want to learn R programming language or Beginners who want to learn R syntax or Beginners who want to learn how to write code in R or Beginners who want to learn how to visualise data in R or Beginners who want to learn how to use R for statistics or Beginners who want to learn the building blocks of programming such as loops, functions and conditional statements.
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Summary
Title: R programming for Beginners
Price: $59.99
Average Rating: 4.81
Number of Lectures: 39
Number of Published Lectures: 39
Number of Curriculum Items: 40
Number of Published Curriculum Objects: 40
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will Learn
- Students will learn the fundamentals of R programming
- Students will learn how to write functions, loops and conditional statements
- Students will learn data visualisation in R
- Students will learn Statistics in R
- Students will learn how to write code in R
- Students will gain knowledge about R syntax and language
Who Should Attend
- Beginners who want to learn R programming language
- Beginners who want to learn R syntax
- Beginners who want to learn how to write code in R
- Beginners who want to learn how to visualise data in R
- Beginners who want to learn how to use R for statistics
- Beginners who want to learn the building blocks of programming such as loops, functions and conditional statements
Target Audiences
- Beginners who want to learn R programming language
- Beginners who want to learn R syntax
- Beginners who want to learn how to write code in R
- Beginners who want to learn how to visualise data in R
- Beginners who want to learn how to use R for statistics
- Beginners who want to learn the building blocks of programming such as loops, functions and conditional statements
The “R Programming for Beginners” course covers a wide range of fundamental topics related to learning and using the R programming language for data analysis and visualization. Here’s a breakdown of the main topics covered in the course:
1. **Installing R software:** Students learn how to install the R programming environment on their computers, which is the first step in getting started with R.
2. **Basic syntax:** The course covers the basic syntax of the R language, which includes understanding how to write and execute simple R commands.
3. **Variable definition:** Students learn how to create and manipulate variables to store data and values in R.
4. **Operators in R:** This topic covers various types of operators in R, including arithmetic, comparison, and logical operators.
5. **Conditionals:** Students learn how to use conditional statements (if-else) to make decisions in their R programs based on certain conditions.
6. **Loops:** The course covers different types of loops (such as for loops and while loops) that allow students to repeat tasks and operations.
7. **Functions:** Students learn how to define and use functions in R, which allow them to encapsulate code into reusable blocks.
8. **Data structures:** The course introduces various data structures in R, such as vectors, matrices, data frames, and lists.
9. **Visualization of data:** Students learn how to create visualizations using R to represent data graphically.
10. **Descriptive statistics:** The course covers essential descriptive statistics, including measures like mean, median, standard deviation, and more.
11. **Statistical analysis:** Students are introduced to statistical techniques like correlation, linear regression, and logistic regression for analyzing relationships and making predictions from data.
12. **Data interfaces:** The course likely covers how to import data from CSV and change working directory.
The overall goal of the course is to provide beginners with a solid foundation in R programming and data analysis techniques. By the end of the course, students will be able to write and understand R code, write programs using loops, conditional statements and functions, create data visualizations, and conduct statistical analyses.
At the end of the course there is a final project that will help people practise what they have learnt. This project requires students to analyse data, allowing students to practically apply their knowledge, bolstering their skills and confidence. This emphasis on real-world application ensures students can adeptly handle data analysis tasks beyond the course.
Course Curriculum
Chapter 1: Downloading and Installing R and R studio
Lecture 1: Downloading R and R studio
Lecture 2: R and R studio installation
Chapter 2: Introduction to R studio
Lecture 1: Introduction to R studio
Chapter 3: Basic Syntax in R
Lecture 1: Printing in R
Lecture 2: Assigning Values in R
Chapter 4: Data Types
Lecture 1: Data Types
Chapter 5: Operators in R
Lecture 1: Arithmetic Operator
Lecture 2: Relational Operator
Lecture 3: Logical Operators
Lecture 4: Assignment Operators
Lecture 5: Miscellaneous Operators
Chapter 6: Conditional Statements in R
Lecture 1: If Statements
Lecture 2: If statement with AND or OR
Lecture 3: If Else statement
Lecture 4: If else if and else statements
Lecture 5: Switch statements
Chapter 7: Loops
Lecture 1: For Loops
Lecture 2: Repeat Loops
Lecture 3: While Loops
Chapter 8: Functions in R
Lecture 1: In built functions in R
Lecture 2: Simple Functions
Lecture 3: Functions with arguments
Lecture 4: Simple functions that return values
Lecture 5: Functions with arguments that return values
Chapter 9: Data Structures
Lecture 1: Vectors
Lecture 2: Lists
Lecture 3: Matrices
Lecture 4: Arrays
Chapter 10: Data Visualisation
Lecture 1: Line Plot
Lecture 2: Bar Plot
Lecture 3: Scatter Plot
Lecture 4: Histogram Plot
Lecture 5: Box Plot
Chapter 11: Descriptive Statistics in R
Lecture 1: Descriptive Statistics
Chapter 12: Data Analysis
Lecture 1: Correlation
Lecture 2: Linear Regression
Lecture 3: Logistic Regression
Chapter 13: Data Interface
Lecture 1: Look up and set directory
Lecture 2: Import CSV
Chapter 14: Practise Exercise
Instructors
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Ricky Lahiri
Data Scientist, Digital Marketer and Doctoral Student.
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- 4 stars: 3 votes
- 5 stars: 5 votes
Frequently Asked Questions
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Can I take my courses with me wherever I go?
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