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 data engineering and machine learning


Data Engineering and Machine Learning using Spark

#artificialintelligence

Organizations need skilled, forward-thinking Big Data practitioners who can apply their business and technical skills to unstructured data such as tweets, posts, pictures, audio files, videos, sensor data, and satellite imagery and more to identify behaviors and preferences of prospects, clients, competitors, and others. In this short course you'll gain practical skills when you learn how to work with Apache Spark for Data Engineering and Machine Learning (ML) applications. You will work hands-on with Spark MLlib, Spark Structured Streaming, and more to perform extract, transform and load (ETL) tasks as well as Regression, Classification, and Clustering. The course culminates in a project where you will apply your Spark skills to an ETL for ML workflow use-case. NOTE: This course requires that you have foundational skills for working with Apache Spark and Jupyter Notebooks.


Technical Lead, Data Engineering and Machine Learning at Thrive Global

#artificialintelligence

Thrive Global is changing the way people live through our behavior change platform and apps used to impact individual and organizational well-being and productivity. The marriage of data and analytics, our best-in-class content and science-backed behavior change IP will help people go from knowing what to do to actually doing it, enabling millions of consumers to begin the Thrive behavior change journey. As a technical lead on Thrive's Data Science and Analytics team, you will play a significant role in building Thrive's platform and products.