"Hands on Training"
"Unleashing the power of R: Advanced Data Analysis and Visualization Techniques"
MODE
Virtual (Google Meet)
TYPE
Mentor Based Workshop
LEVEL
Beginner to Advanced Level
DURATION
10 Hours
TIMINGS
IST 11:00 AM - 12:00 PM
About Workshop:
The beginner's R programming workshop is designed for those new to R and aims to provide a solid foundation in R programming and data analysis. Participants will learn the basics of the language and data analysis techniques, and gain hands-on experience working with real-world data sets. The workshop will provide participants with the skills and knowledge they need to continue learning R programming on their own.
The advanced R programming workshop is designed for those who already have some experience with R and aims to build on the concepts learned in the beginner's workshop. Participants will learn advanced data manipulation and visualization techniques, advanced statistical analyses, handling large datasets, and reproducible data analysis workflows. The workshop will provide participants with the skills and knowledge they need to perform more complex data analysis tasks and apply R in specific domains such as bioinformatics, text mining, and machine learning.
Workshop 1: R Programming for Beginners: Basic Level
What you will learn?
- Day 1- Installing R and R Studio, R data types, R data structures - vector
- Day 2- R data structures - list, data frames
- Day 3
- Control Flow in R - if else, for loop
-Apply family of functions in R and Determining the sequence composition of DNA, Protein and Primer Quality Control with R - Day 4- Data analysis and graphs in base R
Workshop Objectives:
- Introducing participants to the R programming language and its basic syntax and data structures.
- Showing participants how to import, manipulate, and summarize data using R.
- Teaching participants how to create basic visualizations using R, such as bar charts, line plots, and scatter plots.
- Familiarizing participants with commonly used data analysis techniques, such as descriptive statistics, correlation, and linear regression.
- Providing participants with hands-on experience working with real-world data sets to apply the concepts learned in the workshop.
- Giving participants the skills to continue learning R programming on their own and to use it for data analysis in their respective fields.
- Familiarizing participants with the R environment and its packages to perform more advance data analysis and visualization.
Workshop 2: R Programming: Advanced Level
What you will learn?
- Day 1- R libraries - installation - and Dplyr library
- Day 2- ggplot2 - The Grammar of Graphics - Bar graph
- Day 3- Box plot and Violin plot
- Day 4- Sequence analysis with seqinr and shortread library - Bioconductor
Workshop Objectives:
- Reviewing the basics of R programming and data analysis, and building on that foundation to cover more advanced topics.
- Covering more complex data manipulation techniques, such as reshaping and joining data sets.
- Introducing participants to advanced data visualization techniques, such as creating interactive plots, and using specialized visualization libraries like ggplot2, lattice, and Shiny.
- Teaching participants how to perform more advanced statistical analyses, such as generalized linear models, mixed-effects models, and time series analysis.
- Showing participants how to use R to handle and analyze large datasets, such as big data sets, and distributed computing with parallel computing libraries.
- Teaching participants how to create reproducible data analysis workflows and document them using R markdown and other tools.
- Showing participants how to use R in specific domains such as bioinformatics, text mining, and machine learning.
Fee Plan
27th Feb - 02nd Mar
Workshop 1
Basic
03rd Mar-06th Mar
Workshop 2
Advanced
27th Feb - 06th Mar
Combo
Basic &
Advanced
Skills you will Gain
Attendees of the workshop will gain a number of skills, including:
- Advanced data manipulation and preparation techniques
- Advanced data visualization techniques using specialized libraries
- Creating reproducible data analysis workflows and documenting them using R Markdown and other tools
- Applying R in specific domains such as bioinformatics, text mining, and machine learning
- Familiarity with R packages and libraries for advanced data analysis and visualization
- Ability to analyze and interpret complex data sets and make data-driven decisions
Intended For: students, researchers, data analysts, data scientists, academicians and professionals in various fields such as bioinformatics, biotechnology, life sciences, healthcare, marketing, and social science.
Workshop Outcomes
For the beginner's workshop, the outcomes include:
- Understanding the basics of R programming and its syntax
- Ability to import, manipulate, and summarize data using R
- Ability to create basic visualizations using R
- The skills and knowledge to continue learning R programming on their own and to apply it to their own data analysis projects
For the advanced workshop, the outcomes include:
- Reviewing the basics of R programming and building on that foundation to cover more advanced topics
- Advanced data manipulation techniques, such as reshaping and joining data sets
- Advanced data visualization techniques, such as creating interactive plots, and using specialized visualization libraries
- Handling and analyzing large datasets, such as big data sets, and distributed computing with parallel computing libraries
- Creating reproducible data analysis workflows and documenting them using R markdown and other tools
- Applying R in specific domains such as bioinformatics, text mining, and machine learning
