Welcome to the R Programming Course of InstaDataHelp Analytics Services, your gateway to the captivating world of data analysis, visualization, and statistical modeling. R is not just a programming language; it’s a powerful tool that empowers you to unlock the insights hidden within data, whether you’re a data scientist, researcher, or aspiring analyst.
In this course, we’ll embark on an exciting journey through the realms of R, from the foundational principles to advanced data manipulation techniques. Whether you’re a novice with no prior coding experience or an experienced programmer seeking to expand your data analytics skills, this course is tailored to your needs.
Our exploration commences with the essentials, introducing you to R’s syntax, data structures, and data importation. You’ll learn how to clean and prepare data, visualize it using the versatile ggplot2 package, and perform statistical analyses with ease.
As we delve deeper, we’ll cover advanced topics like machine learning, exploratory data analysis (EDA), and even web scraping with R. Each week, you’ll gain practical hands-on experience through labs and projects.
By the end of this course, you’ll be well-versed in using R as a formidable tool for extracting valuable insights, making data-driven decisions, and crafting compelling data stories. R is more than just code; it’s your key to deciphering the language of data.
Whether you aspire to advance your career in data science, conduct groundbreaking research, or simply elevate your analytical skills, this course equips you with the knowledge and proficiency to excel in the data-driven world. Join us on this transformative journey into the R universe, where data analysis becomes a dynamic adventure. Let’s dive into R together!
Below is an overview of the course structure.
Week 1: Introduction to R
- Day 1: Course overview and the importance of R in data analysis
- Day 2: Installing R and RStudio
- Day 3: R basics – variables, data types, and basic operations
- Day 4: Data structures in R (vectors, matrices, data frames)
- Day 5: Hands-on lab – Introduction to R and basic data manipulation
Week 2: Data Import and Cleaning
- Day 6: Reading and writing data in R (CSV, Excel, JSON)
- Day 7: Data exploration and summary statistics
- Day 8: Handling missing data and outliers
- Day 9: Data cleaning and transformation
- Day 10: Hands-on lab – Data import and cleaning in R
Week 3: Data Visualization with ggplot2
- Day 11: Introduction to data visualization principles
- Day 12: Building plots with ggplot2
- Day 13: Customizing plots with themes and aesthetics
- Day 14: Creating complex visualizations and faceting
- Day 15: Hands-on lab – Data visualization with ggplot2
Week 4: Statistical Analysis with R
- Day 16: Hypothesis testing and statistical inference
- Day 17: Linear regression analysis
- Day 18: Logistic regression and classification
- Day 19: ANOVA and non-parametric tests
- Day 20: Hands-on lab – Statistical analysis using R
Week 5: Exploratory Data Analysis (EDA)
- Day 21: Principles of EDA and data profiling
- Day 22: Visualizing data distributions and relationships
- Day 23: Cluster analysis and dimensionality reduction
- Day 24: Time series analysis and forecasting
- Day 25: Hands-on lab – EDA and time series analysis in R
Week 6: R Packages and Data Manipulation
- Day 26: Introduction to R packages and CRAN
- Day 27: Data manipulation with dplyr
- Day 28: Reshaping data with tidyr
- Day 29: Combining data frames and merging datasets
- Day 30: Hands-on lab – Advanced data manipulation in R
Week 7: Advanced Topics
- Day 31: Introduction to machine learning with R (caret package)
- Day 32: Text mining and sentiment analysis
- Day 33: Web scraping with R (rvest and RSelenium)
- Day 34: R Shiny for interactive web applications
- Day 35: Hands-on lab – Machine learning and advanced topics
Week 8: R Markdown and Reproducible Research
- Day 36: Introduction to R Markdown
- Day 37: Creating dynamic reports and documents
- Day 38: Version control with Git and GitHub
- Day 39: Collaborative workflows and reproducible research
- Day 40: Final project presentations and course conclusion
The course structure and duration is suggestive. For customized course, please contact us. We will be providing customized course which will be suitable for your organizational goal.
Please contact at info@instadatahelp.com or call at +91 9903726517 to know further about the course.
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