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Welcome to The Multilingual Quantitative Biologist!

Computing

Computing
UNIX and Linux
Shell scripting
Version control with Git
Scientific documents with \(\LaTeX\)
Biological Computing in Python
- Object-Oriented Programming
Biological Computing in R

Basic Data Analyses and Statistics

Basic Data Analyses and Statistics
Data Management and Visualization
Experimental design and Data exploration
Basic hypothesis testing
Linear Models: regression
Linear Models: Analysis of variance
Linear Models: Multiple explanatory variables
Linear Models: Multiple variables with interactions
Model simplification

Advanced Modelling & Statistics Pre-work

Advanced Modelling & Statistics Pre-work
EnE Modelling and Advanced Data Science Pre-work

Ecological & Evolutionary Modelling

Ecological & Evolutionary Modelling
The Metabolic Basis of Ecology and Evolutionary dynamics
Single Populations
- Populations: Practicals
- From consumer–resource dynamics to logistic growth
Species interactions
Competitive dynamics
- Competitive Dynamics: Practicals
Predator–prey dynamics
- Predator–prey dynamics: Practicals
Epidemiological dynamics
- Epidemiological dynamics: Practicals

Advanced Data Analyses and Statistics

Advanced Data Analyses and Statistics
Generalised Linear Models
Model Fitting using Non-linear Least-squares
- Nonlinear least squares (NLLS) in Python
- Microbial Growth rates in R
Model Fitting using Maximum Likelihood

Assignments and Assessments

Assignments and Assessments
MQB Coursework Assessment
The Computing Miniproject

Appendices

Appendices
Tooling and Environments
- Introduction to Jupyter
- Databases
Data Analysis in Python (Optional)
- Data analyses with Python & Jupyter
Maths and Quantitative Foundations
- Mathematical models in Jupyter
- Maths for Biologists
Performance, Scaling, and Compute
- Introduction to High-Performance Computing (HPC)

References

References

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