Theme: Scientific Computing
111 matching courses
Using the Parallel Computing capabilities in MATLAB allows you to take advantage of additional hardware resources that may be available either locally on your desktop or on clusters and clouds. By using more hardware, you can reduce the cycle time for your workflow and solve computationally- and data-intensive problems faster.
In this seminar, we will discuss a range of workflows available to scale MATLAB applications with minimal changes to your MATLAB code and without needing to learn any shell or scheduler programming syntax.
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 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.
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.
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.
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 LinkedIn Learning course, provided by the University of Cambridge's subscription to LinkedIn Learning.
The course can be accessed here.
A recommended LinkedIn Learning course, provided by 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.
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.
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.
Self-taught
Booking not required
This course is part of a suite of MathWorks online courses available to the University of Cambridge.
Create custom visualizations and automate your data analysis tasks.
If you do not already have an account, you will be asked to create one for the MathWorks Academy to access these courses, please use your @cam.ac.uk email address.
This course can be accessed here.
This course is part of a suite of MathWorks online courses available to the University of Cambridge.
Learn MATLAB for financial data analysis and modeling.
If you do not already have an account, you will be asked to create one for the MathWorks Academy to access these courses, please use your @cam.ac.uk email address.
This course can be accessed here.
This course is part of a suite of MathWorks online courses available to the Univeristy of Cambridge.
This course provides a comprehensive introduction to common features and workflows in MATLAB.
If you do not already have an account, you will be asked to create one for the MathWorks Academy to access these courses, please use your @cam.ac.uk email address.
This course can be accessed here.
This course is part of a suite of MathWorks online courses available to the Univeristy of Cambridge.
This course is an introductory tutorial on commonly used features and workflows.
This course can be accessed here.
This course is part of a suite of MathWorks online courses available to the Univeristy of Cambridge.
Get started quickly using deep learning methods to perform image recognition.
This course can be accessed here.
This course is part of a suite of MathWorks online courses available to the Univeristy of Cambridge.
Learn the basics of practical machine learning methods for classification problems.
This course can be accessed here.
This course is part of a suite of MathWorks online courses available to the Univeristy of Cambridge.
Learn the basics of creating, editing, and simulating state machines in Stateflow.
This course can be accessed here.
This course is part of a suite of MathWorks online courses available to the University of Cambridge.
Improve the robustness, flexibility, and efficiency of your MATLAB code.
If you do not already have an account, you will be asked to create one for the MathWorks Academy to access these courses, please use your @cam.ac.uk email address.
This course can be accessed here.
Self-taught
Booking not required
MathWorks are running a series of regular live webinars, tailored to Professors, PhD students & Post-Docs.
Each Wednesday you will discover a technical topic where you can learn about the latest MATLAB capabilities for your research applications.
To register for the sessions click here
These technical sessions will be followed up on Tuesdays with a session covering online teaching, including ready-to-use resources. You will explore how to use MATLAB to increase student engagement in your course.
his is part of a suite of MathWorks online courses available to the Univeristy of Cambridge.
This course is part of a suite of MathWorks online courses available to the Univeristy of Cambridge.
This is an introductory tutorial on commonly used features and workflows.
This course can be accessed here.
This course is part of a suite of MathWorks online courses available to the University of Cambridge.
Learn the theory and practice of building deep neural networks with real-life image and sequence data.
If you do not already have an account, you will be asked to create one for the MathWorks Academy to access these courses, please use your @cam.ac.uk email address.
This course can be accessed here.
This course is part of a suite of MathWorks online courses available to the University of Cambridge.
Use matrix methods to solve systems of linear equations and perform eigenvalue decomposition.
If you do not already have an account, you will be asked to create one for the MathWorks Academy to access these courses, please use your @cam.ac.uk email address.
This course can be accessed here.
Self-taught
Booking not required
This course is part of a suite of MathWorks online courses available to the University of Cambridge.
Get started quickly with basic descriptive statistics and data fitting.
If you do not already have an account, you will be asked to create one for the MathWorks Academy to access these courses, please use your @cam.ac.uk email address.
This course can be accessed here.
This course is part of a suite of MathWorks online courses available to the University of Cambridge.
Get started quickly with an introduction to symbolic math.
If you do not already have an account, you will be asked to create one for the MathWorks Academy to access these courses, please use your @cam.ac.uk email address.
This course can be accessed here.
This course is part of a suite of MathWorks online courses available to the University of Cambridge.
Explore data and build predictive models.
If you do not already have an account, you will be asked to create one for the MathWorks Academy to access these courses, please use your @cam.ac.uk email address.
This course can be accessed here.
This course is part of a suite of MathWorks online courses available to the University of Cambridge.
Use root finding methods to solve nonlinear equations.
If you do not already have an account, you will be asked to create one for the MathWorks Academy to access these courses, please use your @cam.ac.uk email address.
This course can be accessed here.
Self-taught
Booking not required
This course is part of a suite of MathWorks online courses available to the University of Cambridge.
Use MATLAB ODE solvers to numerically solve ordinary differential equations.
If you do not already have an account, you will be asked to create one for the MathWorks Academy to access these courses, please use your @cam.ac.uk email address.
This course can be accessed here.
This course is part of the Scientific Computing series.
This course is aimed at those new to programming, or who have never been formally taught the principles and basic concepts of programming. It provides an introduction to the basic concepts common to most high level languages (including Python, Java, Fortran, C, C++, Visual Basic). The aim of the course is to equip attendees with the background knowledge and confidence necessary to tackle many on-line and printed programming tutorials. It may also help attendees in deciding which programming language is suitable for their programming task.
Knowledge of the concepts presented in this course is a pre-requisite for many of the other courses in the Scientific Computing series of courses (although not for the "Python for Absolute Beginners" course).
This course is part of the Scientific Computing series and is suitable for people who have Python experience equivalent to either of the introductory courses: Introduction for Absolute Beginners or Introduction for Programmers
These sessions consist of a selection of self-paced mini-courses, each taking at most a half-day. Python expert(s) from the UCS will be present to answer questions or address difficulties with these. Attendees can select from the available topics to most closely meet their individual needs. Attendees are welcome to attend more than one session to work through multiple topics. If an attendee finishes a topic with time to spare they may select another, and so on.
This course is part of the Scientific Computing series.
This course is aimed at those new to programming and provides an introduction to programming using Python, focussing on scientific programming. This course is probably unsuitable for those with programming experience, even if it is just in shell scripting or Matlab-like programs. By the end of this course, attendees should be able to write simple Python programs and to understand more complex Python programs written by others.
As this course is part of the Scientific Computing series, the examples chosen are of most relevance to scientific programming.
This course is part of the Scientific Computing series.
This full-day course introduces the Python programming language to those who are already familiar with another high level programing language such as C/C++, Fortran, Java, Perl or Visual Basic. The aim of this course is to give such programmers sufficient familiarity with Python that they can attend any of the more advanced Python courses organised by the Computing service and easily follow any of the widely available Python tutorials on the more complex aspects of the language.
This course covers all the material contained in the "Programming: Python for Absolute Beginners" course, but in a more abbreviated fashion suitable for those who already have significant programming experience. This course does NOT cover the more complex aspects of the language (for such topics see the other Computing Service Python courses), nor is there much explicit discussion of the object oriented features of Python.
If you are an accomplished and experienced programmer you may find this course too slow, you may prefer to self-teach the course rather than attend in person, the full set of notes can be downloaded.
This course is part of the Scientific Computing series.
It is common for a student or researcher to find a piece of software or to have one thrust upon them by a supervisor which they must then build, install and use. It is a myth that any of this requires system privilege. This course demonstrates the building, installation and use of typical software ranging from trivially easy examples (the "configure, make, install" scheme) through to the evils of badly written Makefiles. Common errors and what they mean will be covered and by the end of the course the student should be able to manage their own software without needing to pester their system administrator.
The course is designed to take someone from having no knowledge of the Unix command line to being able to navigate around directories, and doing simple file manipulation. Then some of the more basic commands, will be introduced, including information on how to get more help from the system itself. Finally accessing remote computers by ssh and the most basic of shell scripts will be introduced.
This course is part of the Scientific Computing series.
No previous experience of shell scripting is required for this course; however some knowledge of the interactive use of the bash shell is a prerequisite (see Simple Shell Scripting for Scientists: Prerequisites for details).
This course introduces shell scripting in bash for scientific computing tasks. Day one introduces very basic shell scripts in bash which process the command line in a simple fashion. Day two covers how to write more advanced shell scripts in bash. Day three covers how to make one's shell scripts more robust.
At the end of each day one or more exercises are set. It is VERY IMPORTANT that attendees attempt these exercises before the next day of the course. Attendees should make sure that they have allowed themselves sufficient study time for these exercises between each day of the course.