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This 2-part workshop will introduce participants to an introduction to healthcare data analysis with hands-on exercises.
Sessions will be held from 2pm to 5pm (CT) on Thursday, December 3rd and Thursday, December 10th.
- Use widely available Python libraries to load, clean, explore, and analyze health datasets
- Visualize health datasets using different types of charts
- Describe the strengths and weaknesses of several machine learning methods (e.g., Decision Tree Classifier, K Neighbors Classifier, Gaussian NB, and Random Forest Classifier) and have a workflow for applying these
1. Google account and access to google drive
2. A tablet or computer
3. Experience with Python programming will not be essential for learning these skills.
Code will be available for download in advance of the workshop to enable participants familiar with Python and data programming to replicate the results shown in the examples.
Who should attend?
Clinician scientists, researchers, trainees with an interest in healthcare data will benefit.
$50.00 – Clinician scientists, researchers, trainees
For more information, please contact Mohamed Elgendi.
Registration Cancellation Policy:
A registration refund will be made upon written request on or before November 29, 2020. A $35 administrative fee will be retained. No refunds will be made for cancellations after this date.