Course Overview The importance of Data Science in the world of Bioinformatics is growing rapidly. This course is meticulously designed for biology students and researchers who are new to programming but wish to elevate their research by utilizing the R language for biological data analysis.

What You Will Learn We have structured this curriculum into 3 distinct modules comprising 9 comprehensive classes:

• Module 1: Fundamentals of R Programming

• Gain a clear understanding of R core concepts, including variables, loops, and data structures.

• Learn how to clean and process large datasets effectively using dplyr.

• Module 2: Data Visualization & Bioconductor

• Get acquainted with the powerhouse of bioinformatics: the Bioconductor repository.

• Master the art of creating publication-quality graphs and visualizations using ggplot2.

• Module 3: Statistical Analysis & Case Studies

• Move from theory to practical application.

• Learn methods to run statistical analyses for biological experiments (such as T-tests and ANOVA) and extract meaningful results from RNA-Seq data.

Who Should Attend

• Undergraduate and postgraduate students of Life Sciences (Biotechnology, Genetic Engineering, Microbiology, etc.).

• Researchers who want to move beyond the limitations of Excel and master coding-based analysis.

• Data enthusiasts interested in working with genomics data.

Outcome By the end of this course, you will be able to confidently handle large biological datasets using R, run statistical analyses, and generate professional-quality graphs for your research papers.