Browse or search for courses

7 Characteristics of Resilient People: Bitesize

Learning and Development bitesize resources are short and high impact; including videos, quick tips guides and interactive bitesize modules. Develop your skills and knowledge quickly, easily, when you need. They complement face to face events and more in-depth online modules.

An introduction to the 8 Wastes (Lean methodology), and how to spot hidden waste in your own processes.

https://youtu.be/Jp5gIwr9xAU

These e-learning modules are available via the InforMEA e-learning platform. Information and guidance on ABS and Nagoya Protocol webpage is available on the University website.

Introduction to Access and Benefit Sharing(ABS)
This course provides an introduction to access and benefit-sharing of genetic resource that originate from overseas.
Sign up on the InforeMEA platform. Further details about the syllabus information are available here.

Introductory Course to the Nagoya Protocol
This course provides an introduction to the major components of the Nagoya Protocol.
Please see the syllabus for further details and sign up on the InforeMEA platform.

If you wish, you can take a quiz at the end of the both courses to assess your learning progress. You are required to answer at least 80% of the assessment questions correctly in order to obtain a course certificate.

Research ethics and research integrity are serious issues. All researchers should consider the ethical context of the research being carried out and be able to justify decisions to the wider academic community.

This session aims to help you get think about the ethical considerations of your research by introducing you to the Department of Engineering ethical review process and investigating some case study scenarios.

Academic writing is hard, let us help you find ways to make it easier!

Open to academic writers in all disciplines and at any stage of their writing journeys, our academic writing workshops are filled with motivational tips and tricks and offer a safe and supportive environment in which to share experiences with others. In these workshops, we unpack myths about writing and share ways of approaching and thinking about writing that can make it seem less daunting. The emphasis is firmly on crowdsourcing and learning from one another – we can guarantee you'll pick up some new ideas to try out to keep you motivated. This session is part workshop in which we discuss academic writing and try out some new techniques, part practical group writing session.

Here's a taste of what to expect at these hands-on writing workshops:

• Guidance and advice from experienced academic writers, as they address some common myths and misconceptions about academic writing.
• Tips for staying motivated, tackling large writing projects, and overcoming writer's block.
• Liberate your writing practice by trying out some creative writing exercises.
• Put what you have learned into practice with an hour's group writing time in for the 'Write Here, Write Now' section of the workshop.

This course will provide a detailed critique of the methods and philosophy of the Null Hypothesis Significance Testing (NHST) approach to statistics which is currently dominant in social and biomedical science. We will contrast NHST with alternatives, especially with Bayesian methods. We will use computer code to demonstrate some issues. However, we will focus on the big picture rather on the implementation of specific procedures.

This development programme for generalist and specialist administrators draws on the expertise of senior figures in the University and provides up to date information on the various strands and issues of University strategy and governance. It includes development of some key skills and a project activity, and offers a valuable opportunity to network with administrators from the UAS and other departments and institutions.

• You need to meet the selection criteria for the programme and complete an application form for the programme.
• Applications will require approval by your line manager and will then be reviewed and prioritised by School Secretary, Head of Division and Head of Institution, Registrary as appropriate.
• Please see further information about key themes and speakers on the programme brochure.
• Applications typically open in May each year.

The data we obtain from survey and experimental platforms (for behavioural science) can be very messy and not ready for analysis. For social science researchers, survey data are the most common type of data to deal with. But typically the data are not obtained in a format that permits statistical analyses without first conducting considerable time re-formatting, re-arranging, manipulating columns and rows, de-bugging, re-coding, and linking datasets. In this module students will be introduced to common techniques and tools for preparing and cleaning data ready for analysis to proceed. The module consists of four lab exercises where students make use of real life, large-scale, datasets to obtain practical experience of generating codes and debugging.

Have you received or collected your data (or anticipate doing so!), but are not sure what to do next? This course is designed to equip you with the skills you need to efficiently clean, reformat, and prepare your datasets using Stata. Ideal for social science researchers and analysts who want to use quantitative data for their dissertation or other research project and want to prepare their data efficiently and follow best practices.

Over four interactive sessions, you will master essential techniques for handling missing data, merging and appending datasets, batch processing, and recoding variables. Each session combines concise, focused lectures with practical, hands-on exercises using either your own data or datasets provided by the instructor.

This is a 1-day workshop to equip you with knowledge of large language models (LLMs) for use in scientific research. The course will introduce LLMs and how they work. Next, we’ll discuss approaches to prompting and RAG, along with the methods that are used to finetune LLMs. The day concludes by covering responsible use and the landscape of models that are available to researchers with some of their pros and cons. After taking this workshop, you will be more confident to take the first steps in using LLMs in your own research.

Participants will require some background knowledge for this course. We will be looking at Python code and neural networks so familiarity with Python and some knowledge of machine learning and neural networks is required. We won’t be coding during the session, but will share code with you for you to work with after the session.

The fundamental-level course is intended for individuals who seek an overall understanding of the AWS Cloud, independent of specific technical roles. It provides a detailed overview of cloud concepts, AWS services, security, architecture, pricing, and support. This course also helps you prepare for the AWS Certified Cloud Practitioner exam.

This is a free course, register and sign in for the following dates:

19th July 2021
2nd August 2021
16th August 2021
2nd September 2021
13th September 2021

This free training day hosted by Amazon Web Services (AWS) is a hybrid event, with a choice of attending online using Chime in a web browser, or there are 28 places available to attend at Amazon's offices next to Cambridge railway station.

Please confirm your choice of venue by the end of Wednesday (tomorrow) with one final survey:

AWS Immersion Day: confirm your choice of venue

Are you interested in machine learning, but not sure where to start? Join us for this session with an AWS expert and demystify the basics. Using real-world examples, you’ll learn about important concepts, terminology, and the phases of a machine learning pipeline. Learn how you can start unlocking new insights and value for your business using machine learning.

This is a free course, register and sign in for the following dates:

22nd July 2021
30th September 2021

In this introductory course, you will learn about AWS products, services, and common solutions. You will learn the fundamentals of identifying AWS services so that you can make informed decisions about IT solutions based on your business requirements.

This is a free course, register and sign in for the following dates:

26th July 2021
9th August 2021
23rd August 2021
6th September 2021

Learn about AWS's strategy and best practices for performing large-scale migrations. Synthesized from AWS's experience of helping hundreds of enterprise customers move to the cloud, you will learn proven techniques that make migrations successful and tools that will accelerate your migration journey to the AWS Cloud.

This is a free course, register and sign in for the following dates:

30th July 2021
23rd September 2021

This short session will provide an understanding of the principles, tools and techniques involved in Process Analysis with a view to improving business process effectiveness and efficiency. Delegates will have the opportunity to practice using the techniques that they learn via exercises designed to be enjoyable and thought provoking.

This workshop is tailored for postgraduate researchers interested in applying for small-scale funding opportunities, such as attending conferences or organizing events. Geared towards those with limited or no prior experience, it covers the essential considerations of the funding application process, and includes a hands-on exercise to provide practical insights into evaluating funding applications.

The Critical Reading course aims to improve students' ability to read critically and evaluate sources, as well as giving helpful tips about productive reading, note taking and providing a checklist of questions to help them with their reading going forward. It is suitable for all students but aimed mostly at undergraduates.

With the increase in AI-generated imagery using models such as Dall-E, Midjourney and Sora and research applications such as AlphaFold, there has been a surge in workflows incorporating models like Stable Diffusion. These models have potential in research applications including drug discovery, weather forecasting, synthetic speech and medical imaging.

The aim of the session will be to equip you with knowledge of how generative AI and diffusion models work and to share an overview of research applications. The workshop will include short talks from researchers already deploying diffusion models in their research.

Much of the workshop content is conceptual and high-level, and by the end of the day participants will have a firm grasp on how diffusion models work. We won’t be coding during the session, but will share code with you for you to work with after the session.

This training is intended for staff and post graduate students who regularly use DSE to help prevent or reduce the risk of possible health problems arising from computer use. The training is also aimed at those responsible within departments for assisting with the DSE risk assessment process. The course will provide an understanding of the DSE Regulations 1992 (as amended 2002) and discuss employer's and employee's duties regarding the assessment of DSE workstations. There will be theory and a practical demonstration. The training will allow time to discuss some of the common health problems and concerns that may be associated with poor workstation set-up with examples of possible solutions.

This course will provide an introduction to Docker.

Writing research software in Python presents numerous challenges to reproducibility - what version of Python is being used? What about the versions of PyTorch, Scikit Learn or Numpy? Should we use Conda, or venv, or Poetry to manage dependencies and environments? How can we control randomness? Do I have the right version of Cuda Toolkit? In principle, given the same data, and same algorithms and methodology, we should be able to reproduce the results of any given experiment to within an acceptable degree of error. Dealing with the above questions introduces significant problems to reproducing experiments in machine learning. This workshop will explore the use of Docker to help alleviate almost all of these questions. Furthermore, combining Docker, git and GitHub can be a powerful workflow, helping to minimise your tech stack, and declutter your python development experience.

This short course introduces Embodied Inquiry as a research method interested in knowledge generated through the body, not just knowledge of the body. Embodied Inquiry has gained traction as a creative research method capable of challenging the mind-body split and exploring the possible role of the body in research, both for the researcher and for participants. The course will provide a broad overview of the theoretical grounding for embodied inquiry, what embodied inquiry can look like within the social sciences as well as the benefits and pitfalls of embodied inquiry as a method. In addition, the course will provide opportunities to consider how embodied inquiry might relate to individual’s research projects and identifying where to find out more about embodied inquiry.

This practical programme is only for those who are scheduled to begin supervising in the next few months; it is not for those who - at this point - have a general interest in learning more about supervisions but have not arranged to start supervising.

This workshop is the second component of a three-part programme, which is designed to be completed in the following order:

1. A self-paced online module containing information on the Cambridge supervision system and introducing the principles and practices of effective teaching and learning, which must be completed before attending this workshop.

2. This in-person workshop that incorporates personal reflection on teaching practice, design of learning activities, discussion of real teaching scenarios, a chance to discuss and ask questions and access to practical information about organising and carrying out your supervisions.

3. An optional follow-up session for those who wish to explore further after gaining some supervision experience.

Please note that everyone new to supervising undergraduates at Cambridge must complete this course: both the online module and the workshop (or equivalent face-to-face training provided by your Department or Faculty).

This practical programme is only for those who are scheduled to begin supervising in the next few months; it is not for those who - at this point - have a general interest in learning more about supervisions but have not arranged to start supervising.

This workshop is the second component of a three-part programme, which is designed to be completed in the following order:

1. A self-paced online module containing information on the Cambridge supervision system and introducing the principles and practices of effective teaching and learning, which must be completed before attending this workshop.

2. This in-person workshop that incorporates personal reflection on teaching practice, design of learning activities, discussion of real teaching scenarios, a chance to discuss and ask questions and access to practical information about organising and carrying out your supervisions.

3. An optional follow-up session for those who wish to explore further after gaining some supervision experience.

Please note that everyone new to supervising undergraduates at Cambridge must complete this course: both the online module and the workshop (or equivalent face-to-face training provided by your Department or Faculty).

This course is designed to provide a basic introduction to how finances are managed at the University and is the ideal first course for anyone who will be working in an accounts area.

Not only does it provide an overview of how the University's Finance System (UFS) is structured but also which activities are performed centrally and which are done in departments. It introduces the concepts of the Financial Regulations and Finance Procedures as well as signposting where you can find more support, how to access UFS and what training may be appropriate for your role.