Apache Spark for Data Engineering and Machine Learning
Offered By: IBM via edX
Course Description
Overview
Apache® Spark™ is a fast, flexible, and developer-friendly open-source platform for large-scale SQL, batch processing, stream processing, and machine learning. Users can take advantage of its open-source ecosystem, speed, ease of use, and analytic capabilities to work with Big Data in new ways.
In this short course, you explore concepts and gain hands-on skills to use Spark for data engineering and machine learning applications. You'll learn about Spark Structured Streaming, including data sources, output modes, operations. Then, explore how Graph theory works and discover how GraphFrames supports Spark DataFrames and popular algorithms.
Organizations can acquire data from structured and unstructured sources and deliver the data to users in formats they can use. Learn how to use Spark for extract, transform and load (ETL) data. Then, you'll hone your newly acquired skills during your "ETL for Machine Learning Pipelines" lab.
Next, discover why machine learning practitioners prefer Spark. You'll learn how to create pipelines and quickly implement features for extraction, selections, and transformations on structured data sets. Discover how to perform classification and regression using Spark. You'll be able to define and identify both supervised and unsupervised learning. Learn about clustering and how to apply the k-mean s clustering algorithm using Spark MLlib. You'll reinforce your knowledge with focused, hands-on labs and a final project where you will apply Spark to a real-world inspired problem.
Prior to taking this course, please ensure you have foundational Spark knowledge and skills, for example, by first completing the IBM course titled "Big Data, Hadoop and Spark Basics."
Syllabus
Module 1 – Spark for Data Engineering
-
Spark Structured Streaming
-
GraphFrames on Apache Spark
-
ETL Workloads
-
Hands-on Lab: ETL for ML Pipelines
Module 2 – Spark ML for Machine Learning
-
Spark ML Fundamentals
-
Spark ML Regression and Classification
-
Spark ML Clustering
Module 3 – Final Project
o Lab: Setup & Practice Assignment
o Project Overview
o Lab: Final Assignment Project
o Project Submission & Grading
- Final Quiz
Taught by
Romeo Kienzler
Tags
Related Courses
4.0 Shades of Digitalisation for the Chemical and Process IndustriesUniversity of Padova via FutureLearn A Day in the Life of a Data Engineer
Amazon Web Services via AWS Skill Builder FinTech for Finance and Business Leaders
ACCA via edX Accounting Data Analytics
University of Illinois at Urbana-Champaign via Coursera Accounting Data Analytics
Coursera