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An Introduction to R: Software For Statistical Analysis, with Dr Simon R. White, MRC Biostatistics Unit, and Dr Adam P. Wagner, University of Cambridge.

GNU R is (freely) available for all major platforms (Microsoft Windows, Linux, Mac, etc.) and is growing in popularity in academia and beyond for carrying out statistical analysis and data manipulation.

The aim of the course is to introduce participants to the basics of statistical analysis and the open source statistical software GNU R.

Participants will actively use R throughout the course, during which they will be introduced to principles of statistical thinking and interpretation by example, exercises and discussion about a range of problems. The examples will be used to present a variety of statistical concepts and techniques, with no focus on any specific discipline.

Participants Without a Raven Password: If you do not have a Raven's account and would like to attend this course, or have other booking queries, please email Adam Wagner (apw40@medschl.cam.ac.uk).

Python is a general-purpose programming language used to build just about anything. Python is key for backend web development, data analysis, artificial intelligence and scientific computing, all of which are key for pursuing IT careers.

With PCAP: Programming Essentials in Python you learn to design, write, debug, and run programs encoded in the Python language. No prior programming knowledge is required. The course begins with the very basics guiding you step by step until you become adept at solving more complex problems.

If you already have an active Cisco account you can join the course by clicking here.

This data analytics essentials course teaches you the fundamental tools of a data analyst. You will learn to transform, organize, and visualize data with spreadsheet tools such as Excel. You will also learn how to query data from a relational database using SQL and how to improve your data presentations using powerful business intelligence tools like Tableau. By the end of the course, you will have an analytics portfolio complete with an analysis of the popular movies dataset, showcasing your skills in Excel, SQL and Tableau.

This introductory course takes you inside the world of data science. You will learn the basics of data science, data analytics, and data engineering to understand how machine learning is shaping the future of business, healthcare, education, and more. Data science professionals who can provide actionable insights for data-driven decisions are in high demand all over the world.

This is an introduction to programming in modern C++, based on the book "'Programming: Principles and Practice using C++"' (2nd ed.) by Bjarne Stroustrup. The aim is to teach participants how to write non trivial, practical programs that are comprehensible and portable. Participants should also be able to understand and modify most well-written C++ applications, though not necessarily every aspect of them.

C++ is a large and complicated language, which is reflected in the length of this course. The creator of C++, Prof. Stroustrup, estimates that newcomers to programming will have to devote in excess of 200 hours' of work to learn how to program in C++ properly. Please bear that in mind if signing up for the course. It would also be of help (though not essential) if attendees have some prior programming experience in another language, e.g. Python.

This course is aimed at researchers who want to learn core skills and best practices for scientific computing. It will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.

The course covers the core skills needed to be productive in a small research team:

• Unix command line (and how to automate repetitive tasks);
• Python or R (and how to grow a program in a modular, testable way); and
• version control with Git (and how to track and share work efficiently).

Further information is available here.

Applicants for this course are requested to complete a pre-course survey. This will be used to tailor the course content to the audience research interests and background.

This event is organized in collaboration with Software Carpentry.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

What are the cognitive differences between novices, competent practitioners, and experts? Do different people really have different learning styles? Do flipped classrooms actually work better than regular lectures? This tutorial will explore recent research in these areas and more, and show participants how to apply that research in the classroom to improve teaching.

This tutorial is a condensed version of the instructor training program that Software Carpentry has been running for the past three years. In it, we will explore a handful of research results in educational psychology, and see how to use those findings to build more effective lessons.

Greg Wilson is the Executive Director of the Software Carpentry Foundation, a volunteer non-profit organization that teaches researchers basic lab skills for scientific computing.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

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) in particular.

Practical examples of using the HPCS clusters will be used throughout, although it is hoped that much of the content will have applicability to systems elsewhere.

This course aims to provide a basic knowledge of GPU programming using OpenACC directives. The course is very hands-on oriented, aiming to give to you the opportunity to practice and experiment from the very beginning.

A recommended course by the Digital Literacy Skills Programme as part of the University of Cambridge's subscription to LinkedIn Learning.

The course can be accessed here.

A recommended course by the Digital Literacy Skills Programme as part of the University of Cambridge's subscription to LinkedIn Learning.

The course can be accessed here.

A recommended course by the Digital Literacy Skills Programme as part of the University of Cambridge's subscription to LinkedIn Learning.

The course can be accessed here.

A recommended course by the Digital Literacy Skills Programme as part of the University of Cambridge's subscription to LinkedIn Learning.

The course can be accessed here.

A recommended course by the Digital Literacy Skills Programme as part of the University of Cambridge's subscription to LinkedIn Learning.

The course can be accessed here.

A recommended course by the Digital Literacy Skills Programme as part of the University of Cambridge's subscription to LinkedIn Learning.

The course can be accessed here.

A recommended course by the Digital Literacy Skills Programme as part of the University of Cambridge's subscription to LinkedIn Learning.

The course can be accessed here.

A recommended course by the Digital Literacy Skills Programme as part of the University of Cambridge's subscription to LinkedIn Learning.

The course can be accessed here.

A recommended course by the Digital Literacy Skills Programme as part of the University of Cambridge's subscription to LinkedIn Learning.

The course can be accessed here.

A recommended course by the Digital Literacy Skills Programme as part of the University of Cambridge's subscription to LinkedIn Learning.

The course can be accessed here.

A recommended course by the Digital Literacy Skills Programme as part of the University of Cambridge's subscription to LinkedIn Learning.

The course can be accessed here.

A recommended course by the Digital Literacy Skills Programme as part of the University of Cambridge's subscription to LinkedIn Learning.

The course can be accessed here.

A recommended course by the Digital Literacy Skills Programme as part of the University of Cambridge's subscription to LinkedIn Learning.

The course can be accessed here.

A recommended course by the Digital Literacy Skills Programme as part of the University of Cambridge's subscription to LinkedIn Learning.

The course can be accessed here.

A recommended course by the Digital Literacy Skills Programme as part of the University of Cambridge's subscription to LinkedIn Learning.

The course can be accessed here.

A recommended course by the Digital Literacy Skills Programme as part of the University of Cambridge's subscription to LinkedIn Learning.

The course can be accessed here.