Statistical Analysis with R for Research
A comprehensive course teaching statistical analysis using R for researchers. Covers data manipulation, visualization, hypothesis testing, regression analysis, and reproducible research workflows — equipping researchers with the practical R skills needed to analyze and interpret their data.
Transcriptomics Data Analysis (Bulk + Single Cell)
A live, instructor-led training program covering best practices in high-throughput RNA-seq data analysis. Participants learn to independently analyze gene expression datasets using R, Bioconductor, and the scverse ecosystem — from raw counts to biological interpretation.
Biomarker Identification using Machine Learning
Hands-on course applying advanced machine learning and bioinformatics techniques to identify novel biomarkers from high-dimensional biological data. Focuses on cancer genomics using TCGA data to discover clinically relevant biomarkers for diagnosis, prognosis, and treatment selection.
Pan-Cancer Bioinformatics with R: Ideation to Publication
An intensive training program guiding participants through the complete journey of pan-cancer analysis — from research idea to publication. Covers TCGA data access, expression, survival, mutation, and immune analyses, multi-omics integration, publication-ready visualization, and manuscript preparation.
AI in Drug Discovery: In Silico Toxicology Modeling
A one-day hands-on workshop introducing AI-powered toxicology modeling for drug discovery. Participants build machine learning models to predict compound toxicity, classify molecules, and analyze structure–activity relationships using real-world cheminformatics datasets.
Data Science and Machine Learning for Biologists
Taught at CBLAST, University of Dhaka, this course introduces biologists to data science and machine learning through hands-on biological case studies. Covers data processing, visualization, and analysis using Python and R, with applications of supervised and unsupervised learning in genomics, transcriptomics, and health data.