Data Science for Healthcare Training Overview
This live, online Data Science and Image Processing for Healthcare training course teaches attendees how data science is used to extract innovative and actionable insights from healthcare-related datasets and medical imaging. Participants learn how predictive modeling is used to assess outcomes, needs, and potential interventions. This class also explores medical image analysis which has become an inherent part of medical technology.
Location and Pricing
This course is taught as a private, live online class for teams of 3 or more. All our courses are hands-on, instructor-led, and tailored to fit your group’s goals and needs. Most Accelebrate classes can be flexibly scheduled for your group, including delivery in half-day segments across a week or set of weeks. To receive a customized proposal and price quote for online corporate training, please contact us.
In addition, some courses are available as live, instructor-led training from one of our partners.
Objectives
- Install Anaconda on a personal computer
- Prepare and explore healthcare-related datasets using the primary tools for data science in Python, including NumPy, Pandas, Matplotlib, and Scikit-learn
- Examine many of the unique qualities and challenges of healthcare data
- Understand how data science is impacting medical diagnosis, prognosis, and treatment
- Use a data science approach to evaluate and learn from healthcare data, such as behavioral, genomic, and pharmacological
- Use deep learning and TensorFlow to interpret and classify medical images
- Perform feature extraction, segmentation, and quantitative measurements of medical images
- Understand the increasing importance of data science and image processing in healthcare
Prerequisites
Students must know basic Python programming.
Outline
Expand All | Collapse All
Overview of Data Science in Healthcare
The Data Science Process
How Data Science is transforming the healthcare sector
Essential Python Data Science Libraries
Data Exploration
- Line Chart
- Scatterplot
- Pairplot
- Histogram
- Density Plot
- Boxplot
- Customizing Charts
Performing Exploratory Data Analysis of Healthcare Datasets
Using Scikit-learn to Apply Machine Learning to Healthcare Questions
Introduction to Deep Learning for Medical Image Analysis
Digital Image Processing
Contrast and Brightness Correction Edge Detection
Image Convolution
Using TensorFlow to Interpret and Classify Medical Images
Structured Activity/Exercises/Case Studies
- Perform Exploratory Data Analysis of Healthcare Datasets
- Use Scikit-learn to Apply Machine Learning to Healthcare Questions
- Use TensorFlow to Interpret and Classify Medical Images
Conclusion
Training Materials
All Data Science and Image Processing for Healthcare training students will receive comprehensive courseware.
Software Requirements
- Any Windows, Linux, or macOS operating system
- Python 3.x installed (Anaconda bundle recommended)
- An IDE with Python support (Jupyter Notebook, Spyder, or PyCharm Community Edition)
