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Bioinformatics Training

 

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

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: 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: An introduction to solving biological problems with Python

An introduction to solving biological problems with Python

Description This course provides a practical introduction to Python programming language for the complete novice. Participants are lead through the core aspects of Python illustrated by a series of example programs. Upon completion of the course, attentive participants will be able to write simple...


Read more at: An introduction to Unix shell

An introduction to Unix shell

Description This course offers an introduction to working with Linux . We will describe the Linux environment so that participants can start to utilize command-line tools and feel comfortable using a text-based way of interacting with a computer. We will take a problem-solving approach , drawing on...


Read more at: Data Carpentry in R

Data Carpentry in R

Description In many domains of research the rapid generation of large amounts of data is fundamentally changing how research is done. The deluge of data presents great opportunities, but also many challenges in managing, analyzing and sharing data. Data Carpentry workshops are designed to teach...


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: 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: 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 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: 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: 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: 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: Statistical analysis using R

Statistical analysis using R

Description Statistics are an important part of most modern studies and being able to effectively use a statistical package will help you to understand your results. This course provides an introduction to some statistical techniques through the use of the R language . Topics covered include: Chi2...


Read more at: Statistics bootcamp using R

Statistics bootcamp using R

Description This 4-days bootcamp provides an in depth look at statistical analyses using R . Day 1 aims to introduce R as a tool for statistics and graphics , with the main aim being to become comfortable with the R environment. As well as introducing core R language concepts, this course also...


Read more at: Statistics for Biologists in R

Statistics for Biologists in R

Description This course is intended to provide a strong foundation in practical statistics and data analysis using the R software environment . The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on...