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Learning together

How we learn on this course
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© Wellcome Connecting Science

How to learn on this course

You are going to learn by watching videos, reading articles, completing exercises where you apply the installed bioinformatics tools for yourself, discussing the content with other learners, and checking your understanding using quizzes and a final test.

You should be able to complete majority of steps in this course using an internet browser, but you will also need a Linux operating system based computer to be able to run commands and install software necessary to learn and practice on this course. You will also be handling different languages during this course (Linux/bash and R).

You will probably find it easier to use the tools if you have access to a laptop or computer with a large monitor, rather than a mobile phone or tablet.

We encourage you to have at hand some previously released genomics data (or plan to obtain some) so that you can apply the knowledge gained on this course on your own data straight away. This also includes having a biological question you would like to think about.


During almost every step of the process, you will be able to use the comments area to discuss the course material with other learners. We encourage you to try social learning by sharing your thoughts and ideas. Some of the course’s steps are Discussion Steps. Please take a look at FutureLearn’s Social Learning Tips and FutureLearn’s Learning Guide for more details.

Use these ideas to help you to make comments and to join in the Discussion Steps:

  • Write what you would also say to someone face-to-face
  • Make constructive comments – critique the idea, not the person
  • Remember that other learners vary in culture, age and experience
  • Read your comments and responses through before posting
  • Some learners do not have English as their first language, so always try to write clearly
  • Explain any acronyms you use and avoid jargon if you can

If you read a comment that you think might break FutureLearn’s Code of Conduct, report it to FutureLearn’s moderators for review by clicking the flag button beneath it.

On average, the course should take you about 6 hours a week to do. It may take you more or less time depending on several factors, including your learning preferences, your prior knowledge and experience, and how much time you have available. We encourage you to:

  • Learn when it is best for you, and at a pace that suits you
  • Use the quizzes to help you track your learning, recall and apply key concepts, and reflect upon what you have learnt
  • Remember to press the ‘Mark as complete’ tab as you complete each step

At the end of each week we will share a summary of your key discussion points and give you feedback.

Course facilitation

Even though this course is facilitated for the first three weeks, the Educators won’t be able to join in every discussion themselves or respond to every individual comment, but the course encourages a strong learning community. The learning is focused around debate and discussion – supporting other learners, sharing your own experience and knowledge, and listening to new perspectives. We hope that you will enjoy interacting with and learning from each other in this way. Don’t forget to comment, reply to other learners and ‘like’ comments.

Completing the course and Free Certificate of Achievement

At the end of the course, you will find a test consisting of ten multiple choice questions which cover the material taught in this course.

If you are interested in obtaining a free digital Certificate of Achievement, you will need to score 70% or above on the final test, and complete 90% of the steps in the course. You should try to answer all the final assessment questions. You have three attempts for each question.

Please note this test is not compulsory and does not affect your learning on this course, it is only needed if you would like to claim the Certificate of Achievement at the end of the course.

© Wellcome Connecting Science
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Bioinformatics for Biologists: Analysing and Interpreting Genomics Datasets

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