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Bioinformatics Training

 

These courses aim to provide beginners with an introduction to programming and computing languages (e.g. Matlab, Python, R, Unix), introductory statistics (i.e. Core Statistics in R) and best programming practices.

For all of these courses, the focus is always on how to use programming languages, statistics and best practices to solve biological problems.

Read more at: Introduction to R for Biologists

Introduction to R for Biologists

Description R is one of the leading programming languages in Data Science . It is widely used to perform statistics, machine learning, visualisations and data analyses. It is an open source programming language so all the software we will use in the course is free . This course is an introduction...


Read more at: Introduction to Python for Biologists

Introduction to Python for Biologists

Description This course provides a practical introduction to the writing of Python programs for the complete novice . Participants are lead through the core concepts of Python including Python syntax, data structures and reading/writing files. These are illustrated by a series of example programs...


Read more at: Introduction to working with UNIX and bash

Introduction to working with UNIX and bash

Description Using the Linux operating system and the bash command line interface, we will demonstrate the basic structure of the UNIX operating system and how we can interact with it using a basic set of commands. Applying this, we will learn how to navigate the filesystem, manipulate text-based...


Read more at: High Performance Computing: An Introduction

High Performance Computing: An Introduction

Description The course aims to give an introductory overview of High Performance Computing (HPC) in general, and of the facilities of the High Performance Computing Service (HPCS) available at the University of Cambridge. Practical examples of using the HPCS clusters will be used throughout...


Read more at: An introduction to MATLAB for biologists

An introduction to MATLAB for biologists

Description This course aims to give you an introduction to the basics of Matlab . During the two day course we will use a practical based approach to give you the confidence to start using Matlab in your own work. In particular we will show you how to write your own scripts and functions and how...


Read more at: Reproducible Research with R

Reproducible Research with R

Description This course introduces concepts about reproducibility that can be used when you are programming in R. We will explore how to create notebooks - a way to integrate your R analyses into reports using Rmarkdown . The course also introduces the concept of version control . We will learn how...


Read more at: Data Science in Python

Data Science in Python

Description This course covers concepts and strategies for working more effectively with Python with the aim of writing reusable code , using function and libraries. Participants will acquire a working knowledge of key concepts which are prerequisites for advanced programming in Python e.g. writing...


Read more at: Introduction to Statistical Analysis

Introduction to Statistical Analysis

Description This course provides a refresher on the foundations of statistical analysis . The emphasis is on interpreting the results of a statistical test, and being able to determine the correct test to apply. Practicals are conducted using a series of online apps, and we will not teach a...


Read more at: Managing your Research Data

Managing your Research Data

Description How much data would you lose if your laptop was stolen? Have you ever emailed your colleague a file named 'final_final_versionEDITED'? Have you ever struggled to import your spreadsheets into R? Would you be able to write a Data Management Plan as part of a grant proposal? As a...


Read more at: Introduction to Machine Learning

Introduction to Machine Learning

Description Machine learning gives computers the ability to learn without being explicitly programmed. It encompasses a broad range of approaches to data analysis with applicability across the biological sciences. Lectures will introduce commonly used algorithms and provide insight into their...