All-provider course timetable

Hydrofluoric Acid (HF) is one of the most toxic and potentially dangerous substances used in the University. All users of HF should be fully aware of and have a good understanding of the nature of HF. They should know how best to control HF, avoid accidental exposure and understand how to deal with accidental exposure to HF. All users of HF are strongly advised to attend this course. This course is also useful for First Aiders in Departments where HF is used.

This course complements the supervising training and information your Department will provide. It is a course that consists of: an online module, which introduces practices and principles of undergraduate supervision at Cambridge, and a face-to-face workshop in which you will explore challenges and approaches to supervising.

By the end of this course you will know:

• the purpose of supervisions at Cambridge
• how to deal with common supervision scenarios
• how to provide effective feedback
• the practicalities of starting to supervise

Topics covered:

• Introduction to supervising (including what supervisions are, format, preparing for them)
• Background information for those who need it (British education system, Cambridge undergraduate system)
• Role of a supervisor
• Dealing with different supervision scenarios
• Departmental information
• Summary of what you have learnt
• Practical tips and advice
• Resources for ongoing support and information

This course aims to provide students with a range of specific technical skills that will enable them to undertake impact evaluation of policy. Too often policy is implemented but not fully evaluated. Without evaluation we cannot then tell what the short or longer term impact of a particular policy has been. On this course, students will learn the skills needed to evaluate particular policies and will have the opportunity to do some hands on data manipulation. A particular feature of this course is that it provides these skills in a real world context of policy evaluation. It also focuses primarily not on experimental evaluation (Random Control Trials) but rather quasi-experimental methodologies that can be used where an experiment is not desirable or feasible.

Topics:

• Regression-based techniques
• Evaluation framework and concepts
• The limitations of regression based approaches and RCTs
• Before/After, Difference in Difference (DID) methods
• Computer exercise on difference in difference methods
• Instrumental variables techniques
• Regression discontinuity design.

Are you completely new to Twitter and struggling to start? Or are you already on Twitter but know you could be making better use of it to promote yourself and your library? Join Librarians In Training for an interactive workshop aimed at helping librarians to make the most of their time online.

Offered as part of the Librarians In Training Easter App Hunt this interactive session will give you the chance to enhance your Twitter skills. For those new to the platform there will be guidance on what Twitter can be used for and how to get started whilst those already using Twitter will benefit from learning how to engage library users, promote their service and enhance their own professional network.

The session will include both advice and practical exercises so you can put your new knowledge to the test.

This course has been discontinued. If you have questions, please contact PPD.

PHEP is Cambridge's professional development programme for probationer University lecturers and new College teaching officers. With contributions from academic and key administrative staff from the collegiate University, the seminar provides a platform for orientation and exploration of the opportunities, cultures and conventions of the University of Cambridge.

This course is an essential component of training for new laser users, which should be backed up by practical training in departments.

The course may be suitable for users of other classes of lasers, depending on the risk, but please discuss this with your Laser Safety Officer first.

This compulsory course will equip you with the skills required to manage the research information you will need to gather throughout your graduate course, as well as the publications you will produce yourself. It will also help you enhance your online research profile and measure the impact of research.

This laptop only 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 methods for addressing real-life issues in the biological sciences.

There are three core goals for this course:

1. Use R confidently for statistics and data analysis
2. Be able to analyse datasets using standard statistical techniques
3. Know which tests are and are not appropriate

R is a free, software environment for statistical and data analysis, with many useful features that promote and facilitate reproducible research.

In this course, we introduce the R language, and cover basic data manipulation and plotting. We then move on to explore classical statistical analysis techniques starting with simple hypothesis testing and building up to generalised linear model analysis. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory

After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques.