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Summary of the week 3

summarise w3 and the course
Congratulations on reaching the end of the course!

In the final week of the course, led by Kristy, the focus was on advanced analysis and applications of antimicrobial resistance (AMR) data.

The week covered the benefits and methods of sharing AMR data, accessing public sequence databases, exploring AMR transmission pathways, and using AI and machine learning techniques in research.

We hope the material of the course helped you achieve the learning outcomes defined:

  • Explain the genotypic basis of AMR
  • Contrast and critique the various ways to predict AMR from linked genotype/phenotype data
  • Discuss the various AMR databases and their related pros and cons
  • Explain how different AMR prediction tools can be operated and their outputs interpreted and implemented, understanding the current pitfalls of those tools
  • Describe the process required to create and share FAIR and open AMR data

By now, we hope that you learned how to share data, investigate AMR transmission pathways, and got a clearer picture of how AI and machine learning to better understand AMR mechanisms and transmission. You have also acquired different resources and links to the training that you can pursue after this course.

Here is a reminder about the assessment of learning on 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 will find the test in the next step of this course.
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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Antimicrobial Databases and Genotype Prediction: Data Sharing and Analysis

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