Databricks - Apache Spark for Machine Learning and Data Science

Overview

On this accelerated Databricks Apache Spark for Machine Learning and Data Science course, you’ll learn the fundamentals of Apache Spark and a deeper understanding of how the platform applies to Machine Learning (ML) and Data Science.

In just 2 days, you’ll build knowledge on Spark’s architecture and internals, the core APIs for using Spark, SQL and other high-level data access tools, as well as Spark’s streaming capabilities. You’ll also:

• Gain familiarity with Decision Trees, Random Forests, Gradient Boosted Trees, Linear Regression, Collaborative Filtering, and K-Means
• Perform hyperparameter tuning with cross-validation
• Build a Machine Learning Pipeline using a combination of Transformers and Estimators Save/Restore Models

Through Firebrand’s Lecture | Lab | Review methodology, you’ll get access to courseware, learn from certified instructors and train in a distraction-free environment.

Audience

This course is ideal if you are in any of the following roles:

• Data Scientists and ML Practitioners who are new to Apache Spark and are interested in learning how to employ their skills with the Apache Spark framework
• SQL Analysts interested in growing beyond simple SQL queries and into the use of the DataFrame and Spark-ML APIs
• Data Analysta and Data Engineers that have a data science background and would like a deeper understanding of Spark-ML capabilities