Introduction to Python for Public Health Data Analysis | Brown School at Washington University in St. Louis
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Introduction to Python for Public Health Data Analysis

 

Registration deadline: June 7th

15 CEUs/CPH units

Paul Boal
Vice President of Delivery, Amitech Solutions

This course will introduce students to the fundamentals of the Python language, common Python modules for data manipulation and analysis, and Jupyter notebook environment. The course will begin with how to acquire data from publicly available sources and databases, cleansing and transformation of data, and the creation of descriptive statistics and graphics. The course will
also introduce Python's natural language processing and machine learning modules for basic data classification and predictive modeling applications. Throughout the course, instruction and assignments will promote best practices for creating programs that can be shared and used for reproducible research.

Note: Students taking this class should have experience doing data preparation or data analysis within the last 5 years. This could
be demonstrated through previous work with statisical packages like R, SAS, SPSS, or Stata, or advanced data manipulation and analysis in Excel or Business Intelligence tools such as Tableau or Qlikview. Prior programming experience in Python is not required.


Class size is limited to 15.

$650 General admission
$450 Non-profit/government employees (1st Summer Institute class)
$400 Non-profit/government employees (Additional Summer Institute classes)

This class will include both degree-seeking graduate students and practicing professionals. Individuals registering through Professional Development will receive continuing education units - but not academic credit - for the class.

About the Instructor:

Portrait of Bob Mai

Paul has been architecting healthcare analytics solutions for more than  15 years, implementing a range of technologies from traditional data warehouses to Hadoop-based solutions, advanced analytics, and real-time clinical data integration. Paul is now Vice President of Delivery and Consultant with Amitech Solutions focused on delivering big data solutions for the healthcare industry. His data management expertise includes work with numerous relational database management systems (Oracle, DB2, MySQL, PostgreSQL, Redshift and Teradata) and non-relational systems (MongoDB, HBase, SOLR, Cache and Neo4J). Boal speaks and teaches for The Data Warehouse Institute and has presented at numerous industry conferences including TDWI, StampedeCon, and Hadoop Summit.

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