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Overview
Learn the fundamental skills of working with EHR data in order to build and evaluate compliant, interpretable machine learning models that account for bias and uncertainty using cutting-edge libraries and tools including Tensorflow Probability, Aequitas, and Shapley. Understand the implications of key data privacy and security standards in healthcare. Apply industry code sets, transform datasets at different EHR data levels, and use Tensorflow to engineer features. The Applying AI to EHR Data program is offered by Udacity.
Course Skills
- Medical code sets
- Shapley value
- Feature engineering
- TensorFlow
- Healthcare privacy regulations
- ETL
- Model uncertainty estimation
- Exploratory data analysis
- Model bias analysis
- Data splitting
- Model performance metrics
- Tensorflow dataset API
- Aequitas
- Tensorflow probability library
Programme Structure
Courses include:
- EHR Data Security and Analysis
- EHR Code Sets
- EHR Transformations & Feature Engineering
- Building, Evaluating and Interpreting Models
- Project: Patient Selection for Diabetes Drug Testing
Key information
Duration
- Part-time
- 2 days
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
Campus Location
- Mountain View, United States
Disciplines
Data Science & Big Data View 468 other Short Courses in Data Science & Big Data in United StatesWhat students do after studying
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Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
Prior to enrolling, you should have the following knowledge:
- Data cleaning
- Machine learning frameworks in Python
- Basic supervised machine learning
- Intermediate Python
Tuition Fees
Additional Details
- This program can be paid for with the Udacity subscription.
Funding
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