Essential Maths

Graphs

Indices, logs and exponentials

Differentiation 1

Differentiation 2

Differentiation 3

Integration 1

Integration 2

Complex numbers

Differential equations 1

Differential equations 2

Differential equations 3

Linear algebra 1

Linear algebra 2

Systems of differential equations 1

Systems of differential equations 2

Systems of differential equations 3

Probability 1

Probability 2

Probability 3

A course in maths, containing a primer in everything you need to know in order to analyse systems of differential equations.


See the individual days for links to training material content.

Foundational Introduction to High Performance Computing

This course aims to introduce the principles of high performance computing (HPC) systems, how they operate, and how we can utilise the computing power they can offer to model complex systems.

Introduction to OpenMP and MPI

This course pilot will introduce the parallelisation technologies OpenMP and MPI, including the fundamentals and practicalities of using them to parallelise C programs to increase their performance.

test

Procedural Programming

Variables

Functions

Containers

Arrays

Procedural Programming is based around the idea that code should be structured
into a sequence of **procedures** that operate on data. This course will
introduce you to the basics of procedural programming in either Python or C++.


Object-Orientated Programming

Classes

Inheritance and Composition

Polymorphism

The Object Oriented Paradigm builds upon the Procedural Paradigm, but builds code around data.
This course will introduce you to the basics of Object Oriented Programming in either Python or C++.


Functional Programming

State and Side Effects

Side Effects

Recursion

Higher Order Functions

Functional Programming is based around the idea that programs are constructed
by applying and composing/chaining **functions**. This course will introduce
you to the basics of functional programming in either Python or C++.


Software Architecture and Design

Programming design concepts and patterns, such as procedural, object-orientated, functional, generic. Covers data structures, memory allocation, ownership.


The Bash shell

Introducing the Shell

Files and Directories

Creating Things

Pipes and Filters

Shell Scripts

Loops

The Bash shell is a command-line interface used in Unix-based operating systems
such as Linux and macOS. This course will introduce you to the basics of using
the Bash shell.


Version Control

Automated Version Control

Setting Up Git

Creating a Repository

Tracking Changes

Exploring History

Remote Repositories

Branches

Ignoring Things

This course introduces the basics of version control using the Git version control system.
We will learn how to setup Git, and use it to track changes in our code.


Packaging and Dependency Management

Packaging Python Projects

Making Packages

Reusing Packages

Sharing Packages

Virtual Environments

Introduction to CMake

This course introduces the basics of packaging and dependency management in Python and C++.
For Python, we introduce `venv` for virtual envronments, and `pip` for package management and how to structure a modern Python package and publish it to PyPI.
For C++, we introduce the CMake build system and how use it to manage dependencies and the build process.


Best Practices

Code Style

Linters

This course covers how to style your Python code, and use linters to enforce a consistant style and highlight any code that can lead to commonly encountered bugs or problems.


IDEs

VSCode

Integrated Development Environments (IDEs)provide programmers with a complete development environment to
write, edit, debug, and deploy their code. This course introduces the popular VSCode IDE, both for Python
and C++ development.


Testing

Automated Testing

Diagnosing Issues

Scaling Up Unit Testing

Testable Code and Fixtures

Using Mocks in Tests

This course introduces the basics of automated testing and debugging in Python, using the Pytest framework.


Containerisation with Docker

Introduction

Docker Command Line

Cleaning Up Containers

Running-containers

Finding Containers on Docker Hub

Creating Containers

More Complex Containers

Examples

Using Docker with Github Actions

Using Docker with Jekyll

Reproducibility and Granularity

Setup

This course aims to introduce the use of Docker containers with the goal of
using them to effect reproducible computational environments.


Snakemake Tutorial

Basics: An example workflow

Advanced: Decorating

Additional features

Short tutorial

This tutorial introduces the text-based workflow system
Snakemake.


Technology and Tooling

Basic tools like bash, version control, containers, IDEs, and snakemake.


Collaboration on GitHub

Git Refresher

Collaborative Worklow

Issue Management

This course will show you how to use Git for effective collaboration with others
using the GitHub platform. After completion of the course, you will be able to
contribute to projects on GitHub, including opening issues and pull requests.


Continuous Integration

GitHub Actions

Code Coverage

Documentation

This course introduces the concept of continuous integration and how to set it up for a Python project using GitHub Actions.


Software Project Management

Courses on software project management such as on collaborative programming and continuous integration.


Setting Up a Training Slurm Cluster on AWS

How to setup a minimal Slurm cluster

Material covering how to setup a Slurm cluster for trainees to use during the courses in this theme. Currently uses AWS and Flight Solo.


Introduction to High Performance Computing

Why Use a Cluster?

Connecting to Remote HPC systems

Exploring Remote Resources

Introduction to Job Scheduling

Accessing Software via Modules

Transferring Files with Remote Computers

Running a parallel job

Using Resources Effectively

Using Shared Resources Responsibly

An introduction to high-performance computing (HPC), covering connecting to HPC resources and the slurm job scheduler.


Introduction to Parallelism

This session introduces the basics of parallelisation and parallel programming, covering shared and distributed memory, different parallel paradigms, and the distinctions between data parallelism and message passing.


HPC Scalability Profiling

Understanding Code Scalability

Scalability Profiling

This session introduces the concept of scalability and how to profile the scalability of your code with an increasing number of cores.


Introduction to the Message Passing Interface

Communicating Data in MPI

Point-to-Point Communication

Collective Communication

Non-blocking Communication

Derived Data Types

Porting Serial Code to MPI

Optimising MPI Applications

Common Communication Patterns

Advanced Communication Techniques

This session introduces the Message Passing Interface (MPI), teaching trainees how to use the MPI API for compiling and running applications across multiple processes. It covers point-to-point and collective communication, non-blocking functions, and handling non-contiguous memory with derived data types. Attendees will practice converting serial code to parallel, understanding scaling performance, and using profilers to optimise MPI applications.


Parallel Programming with OpenMP

Introduction to OpenMP

Parallelisation with OpenMP

Synchronisation and Race Conditions

Introduction to Hybrid Parallelism

This session covers the fundamentals of OpenMP, including its API, compilation, and execution. Participants will learn to parallelise their programs using OpenMP's pragma directives, manage threads, and control variable scoping and loop scheduling. The session also addresses thread synchronization, race conditions, and the use of hybrid parallelism with OpenMP and MPI.


High Performance Computing

An introduction to high-performance computing (HPC), covering connecting to HPC resources, job schedulers (also known as batch systems), and techniques for determining the scalability of code on HPC resources.


Intro to Python

Running Python

Variables and Types

Writing and running Python from an IDE

Built-in Functions and Help

Libraries

Analyzing and Visualizing Data

Pandas Dataframes

Lists

For Loops

Conditionals

Looping Over Data Sets

Errors and Exceptions

Writing Functions

Variable Scope

Project: Snake Game

This course introduces the basics of programming in Python.
We will learn how to run Python code, and how to use variables, functions, and control flow.
We will also learn how to use Python for data analysis and visualization.


Introductory Courses

Introductory courses on programming languages.


Linear Algebra Solvers

Matrix form of equations

Gaussian Elimination

LU decomposition

Cholesky decomposition

QR decomposition

This course covers the basics of linear algebra focusing on the solution of
dense systems of linear equations using direct methods and matrix
decompositions. Both the theory and implementation of these methods are
covered, as well as some standard Python libraries for linear algebra.


Sparse Matrices and Iterative Solvers

Sparse Matrices

COOrdinate format

Finite Difference Matrix

Scipy.sparse and problems

Jacobi and Relaxation Methods

Krylov subspace methods and CG

This course covers the basics of iterative methods for
solving linear systems, and how to use sparse matrices to represent and solve
these systems efficiently.


Non-linear Optimisation

Line Search Methods

Trust Region Methods

Derivative-free methods

Nelder-Mead method

Solving ODEs

ODE Solvers - AM Exercises

ODE Solvers - PM Exercises

Scientific Computing

Courses on scientific computing on subjects including linear algebra, ode solving, bayesian statistics etc.


Essential Maths

Why Maths?

Data analysis

Describe the behaviour of systems

Vital for dynamic and nonlinear systems

Course aims

Topics covered