📚 Syllabus & Course Curriculum
Bioinformatics & Computational Biology
Module-by-module breakdown of Hands-On Single-Cell & Spatial Omics with AI, from foundations to a certified capstone project.
Workflow
• Alignment and quantification with Cell Ranger or alevin-fry
• Empty droplet detection, doublet removal and QC thresholds
• Normalisation choices and their effect on downstream clustering
Analysis
• Dimensionality reduction, neighbourhood graphs and clustering resolution
• Marker detection and the circularity of clustering then testing
• Automated cell-type annotation and reference-based label transfer
Spatial
• Platform differences: spot-based versus imaging-based resolution
• Deconvolution of mixed spots using single-cell references
• Spatial domain identification and neighbourhood analysis
Inference
• Trajectory and pseudotime inference with honest uncertainty
• Cell-cell communication inference and its strong assumptions
• Differential abundance and compositional analysis across conditions
Practice
• Scanpy and Seurat workflows and object interoperability
• Compute and memory management for large atlases
• Sharing analyses and depositing data to community standards
Earn government-registered certification in Hands-On Single-Cell & Spatial Omics with AI
e-Certificate and e-Marksheet issued on successful completion.
