5203 - Data Generation Biomedicine

5203 - Data Generation Biomedicine

Issued by GAIn® - The Global AI network

The purpose of this course is to provide insight into how biomedical data is generated, the ways it affects data analysis, and recipes for avoiding data generation mistakes during experiment planning. This detailed two-day course walks you through nice aspects of the data generation process: from estimating resources needed, planning study design, and choosing the methods/platforms to evaluation of data quality, identification of technical and biological biases, and practical aspects of (meta-)d

Skills

  • Data Analysis
  • Data handling
  • Planning experiment
  • Statistics

Earning Criteria

  • Knowing the data – scale and nature of biomed data. Estimate resources needed, strong and weak points of analog and digital data in biomedicine.
  • Increasing utility of your data – concepts of data annotation and sharing. Explore existing data deposited in the public domain, and identify variables critical for data interpretation.
  • Planning of data collection – efficiency of different technologies and platforms and experimental design. Identify best methods and robust experimental designs before proceeding to experiment.
  • Evaluation of data quality – avoiding troubleshooting contributed by low-quality data. Learn universal and platform/method-specific hallmarks of failed biomedical experiments from raw data.
  • Exam