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March 2022 Data Science for Science Residency - Accelerate Programme

Closing date: 
Monday, 24 January 2022

PhD students and postdocs across Cambridge University can apply for this funded training course, which will equip them will skills in data science for science.

We are offering PhDs and postdocs from across Cambridge University a funded 'Data Science for Science' training course. Aimed at helping participants apply data science tools to their own datasets and research problems, the course runs over five weeks, starting on 7 March 2022. Previous courses have attracted participants from fields including chemistry, biochemistry, physics, engineering, medicine, veterinary medicine and psychology. Applications for the next course are open until 9am on 24 January 2022.

What does the course cover?

The course aims to give researchers in fields outside computer science the skills they need to use machine learning (ML) in their research, and help them apply data analysis to their own datasets and problems. On the course, you will: use data science techniques on your own datasets and research questions; collaborate on real-world data science challenges in teams; and contribute to a world-leading community of scientists and researchers. You can read more about how once of our recent participants has used the course to advance her work here.

Residents will cover 6 modules over a period of 5 weeks:

  • Introduction to Python (preparatory module)
  • Data Processing with Pandas
  • Data Visualisation
  • Web Scraping, JSON and APIs
  • Introduction to machine learning
  • Project & presentation

Full details

About us

The Cambridge Centre for Data-Driven Discovery (C2D3) brings together researchers and expertise from across the academic departments and industry to drive research into the analysis, understanding and use of data science and AI. C2D3 is an Interdisciplinary Research Centre at the University of Cambridge.

  • Supports and connects the growing data science and AI research community 
  • Builds research capacity in data science and AI to tackle complex issues 
  • Drives new research challenges through collaborative research projects 
  • Promotes and provides opportunities for knowledge transfer 
  • Identifies and provides training courses for students, academics, industry and the third sector 
  • Serves as a gateway for external organisations 

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