Streaming analytics basics for Python developers
Lab 1: create a simple Python application
Lab 2: handle a variety of patient data
Lab 3: anonymize and average data
Lab 4: visualize data in a Python notebook
Imagine you work for the IT department in a hospital and want to tap the life-saving potential of continuous data coming in from patients’ vital sign monitors. A Streams application, processing such data in real time, could make swift detections of dangerous anomalies of vital signs, and alert hospital staff when a patient needs immediate care.
IBM® Streams® is an advanced stream processing platform that can ingest, filter, analyze, and correlate massive volumes of continuous data streams. Viewing and analyzing this data helps you make decisions while events are happening.
Development in Streams has traditionally been done by using the Streams Processing Language (SPL). However, with the introduction of the Python Application API, developers like you can create streaming applications by using the Python language without first having to learn SPL. This course introduces you to the IBM Streams Python Application API.
Data Science Experience has been renamed Watson Studio. The videos and instructions in this course still refer to Data Science Experience, but you should still be able to complete the course using Watson Studio. The links might redirect you to the main Watson Studio product page, but if you click the “Start on cloud for free” button on that page, you will be taken to a page where you can create or log in to your IBM Cloud account and begin using Watson Studio, as the course describes.