Programming for Machine Learning (IN-PERSON)

PrerequisitesNew

This course is aimed to provide the tools to create machine learning models in R using the CARET Library. This is a pre-requisite for the intermediate and advanced courses on supervised and unsupervised learning courses.

If you do not have a University of Cambridge Raven account please book or register your interest here.

• ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
• Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
• Attendance will be taken on all courses and a charge is applied for non-attendance, including for University of Cambridge students. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
• Further details regarding eligibility criteria are available here.
• Guidance on visiting Cambridge and finding accommodation is available here.

• Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals

• Participants should be experienced in programming in R as the course will build on this. We recommend the Introduction to R for biologists course as a first course to start programming in R. If you are not able to attend an introductory course, please work through the R material as a minimum.
• Principles of Machine Learning (unless participants already are familiar with the techniques covered)

Number of sessions: 1

• Revision of data manipulation and presentation in R
• Analysing data using random forests
• Analysing data using support vector machines
• Analysing data using neural networks
• Analysing data using k-nearest neighbours
• Analysing data using k-means clustering

To get started with analysing data using standard machine learning libraries, although we will not be going into some of the more advanced methods for fine tuning these models.

Presentations, demonstrations and practicals

This is subject to change in line with the training schedule.

• Free for registered University of Cambridge students
• £ 60/day for all University of Cambridge staff, including postdocs, temporary visitors (students and researchers) and participants from Affiliated Institutions. Please note that these charges are recovered by us at the Institutional level
• It remains the participant's responsibility to acquire prior approval from the relevant group leader, line manager or budget holder to attend the course. It is requested that people booking only do so with the agreement of the relevant party as costs will be charged back to your Lab Head or Group Supervisor.
• £ 60/day for all other academic participants from external Institutions and charitable organizations. These charges must be paid at registration
• £ 120/day for all Industry participants. These charges must be paid at registration
• Further details regarding the charging policy are available here

1

several times a year

• Introduction to R for Biologists (IN-PERSON)
• Principles of Machine Learning (IN-PERSON)