• Overview of R
  • History and evolution of R.
  • Key features and applications in data analysis.
• Setting Up R Environment
  • Installing R and RStudio on different operating systems.
  • Navigating the RStudio: Console, Source, Environment, and History panels.

• Introduction to R Syntax
  • Basic syntax, variables, and data types.
  • Arithmetic operations and basic functions.
• Control Flow
  • Conditional statements: if, else, if-else.
  • Loops: for, while, and repeat.
  • Break and next statements.
• Functions
  • Writing and using functions.
  • Arguments and return values.

• Vectors
  • Creating, accessing, and modifying vectors.
  • Vectorized operations.
• Matrices
  • Creating and manipulating matrices.
  • Matrix operations.
• Lists
  • Creating and using lists.
  • Accessing list elements.
• Data Frames
  • Creating, accessing, and modifying data frames.
  • Data frame operations.
• Factors
  • Creating and using factors.
  • Factor levels and reordering.

• Reading Data into R
  • Reading CSV, Excel, and JSON files.
  • Using readr and readxl packages.
• Exporting Data
  • Writing data to CSV, Excel, and JSON files.
  • Using write.csv, write.xlsx, and jsonlite.

• Introduction to dplyr
  • Using select, filter, mutate, arrange, and summarize functions.
  • Grouping data with group_by.
• Data Tidying with tidyr
  • Using gather, spread, separate, and unite functions.
  • Reshaping and tidying data.

• Introduction to ggplot2
  • Understanding the grammar of graphics.
  • Creating basic plots: scatter plots, line charts, bar charts.
• Customizing Plots
  • Adding titles, labels, and themes.
  • Customizing colors, shapes, and sizes.
• Advanced Visualizations
  • Creating faceted plots.
  • Using ggplot2 extensions for specialized plots.

• Introduction to googleVis
  • Understanding the grammar of graphics.
  • Creating basic and advanced plots: scatter plots, line charts, bar charts.

• Calculating Descriptive Statistics
  • Mean, median, mode, variance, and standard deviation.
• Data Summarization
  • Using summary, aggregate, and other summary functions.

• Hypothesis Testing
  • Introduction to null and alternative hypotheses.
  • Performing t-tests and chi-square tests.
• Correlation and Regression Analysis
  • Pearson and Spearman correlation.
  • Simple and multiple linear regression.
  • Logistic regression.

R Programming is a powerful statistical programming language used widely for data analysis, statistical modeling, and data visualization. It is popular among data scientists, statisticians, and researchers for its flexibility and comprehensive suite of tools.

This training is ideal for students, IT professionals looking to upgrade their skills, researchers, data analysts, and anyone interested in data science and analytics. No prior programming knowledge is required, making it accessible to beginners as well.

The course covers a wide range of topics, including:

• Introduction to R and RStudio
• Data types and structures
• Data manipulation and cleaning
• Statistical analysis and modeling
• Data visualization using ggplot2
• Working with databases
• Advanced R programming concepts
• Practical projects and case studies

The training is delivered through both classroom and online modes. Our trainer-led classes provide flexible scheduling options to accommodate your needs. You can choose the mode and timing that best suits your schedule.

The R Programming course spans over 35+ hours of in-depth, trainer-led instruction. The course duration ensures comprehensive coverage of all topics, with flexibility to extend until the syllabus is fully completed.

Our trainers are industry experts with over 15 years of experience in R Programming and data analytics. They bring practical knowledge from various domains such as finance, healthcare, and technology, ensuring a rich learning experience.

For learning R Language candidates should have strong knowledge in theoretical statistics.

Yes, you will receive a course completion certificate from Ampersand Academy upon successfully finishing the training. This certificate validates your expertise in R Programming and can enhance your professional credentials.

We offer comprehensive career assistance, including personalized coaching, resume building, mock interviews, and job placement support. Our goal is to ensure you are well-prepared to secure top positions in the industry.

To get started, contact us to learn more about the course details and to schedule your free demo session. You can reach out to us via phone or email, and our team will assist you with the enrollment process.

We provide comprehensive study materials, including lecture notes, video tutorials, practical exercises, and access to our online learning platform. These resources are designed to support your learning journey and enhance your understanding of R Programming.

Yes, the course includes hands-on projects and real-world case studies. These practical exercises allow you to apply the concepts learned and gain valuable experience working with R Programming in real-world scenarios.

Our trainers provide dedicated support for your project work, helping you to plan, execute, and troubleshoot your projects. This assistance ensures that you gain practical, hands-on experience and build a strong project portfolio.

Yes, we offer free demo sessions for prospective students. These sessions give you a glimpse of our training approach and allow you to interact with our trainers. Contact us to schedule your demo session.

We offer flexible scheduling options for both classroom and online training. Our goal is to accommodate your availability and provide a learning experience that fits your personal and professional commitments.