Azure Spark Databricks Essential Training

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Lynn Langit

2:52:18

54 View

01 - Introduction

01 - Optimize data pipelines.mp4

00:43

02 - What you should know.mp4

00:59

03 - About using cloud services.mp4

00:29

02 - 1. Big Data on Azure Databricks

01 - Meet Databricks Apache Spark clusters.mp4

02:22

02 - Business scenarios for Spark.mp4

01:45

03 - Understand Spark key components.mp4

02:43

04 - Azure Databricks concepts.mp4

05:25

05 - Quick start Use a notebook.mp4

07:07

03 - 2. Core Azure Databricks Workloads

01 - Review Databricks Azure cluster setup.mp4

03:39

02 - Use a Python notebook with dashboards.mp4

06:01

03 - Use an R notebook.mp4

04:00

04 - Use a Scala notebook for visualization.mp4

06:37

05 - Use a notebook with scikit-learn.mp4

11:29

06 - Use a Spark Streaming notebook.mp4

08:53

07 - Use an external Scala library variant-spark.mp4

10:26

04 - 3. Scaling Azure Databricks Workloads

01 - Understand data engineering workload steps.mp4

03:49

02 - Understand cluster configurations.mp4

05:33

03 - Understand Spark job execution overhead.mp4

05:54

04 - Explore optimization control planes.mp4

05:40

05 - Optimize a cluster and job.mp4

04:31

06 - Run a production-size job.mp4

07:32

05 - 4. Data Pipelines with Azure Databricks

01 - Use Databricks jobs and role-based control.mp4

05:37

02 - Use Databricks Runtime ML.mp4

02:52

03 - Understand ML Pipelines API.mp4

04:16

04 - Use ML Pipelines API.mp4

08:39

05 - Use distributed ML training.mp4

09:59

06 - Understand Databricks Delta.mp4

03:41

07 - Use Databricks Delta.mp4

05:10

08 - Use Azure Blob storage.mp4

02:41

09 - Understand MLflow.mp4

07:34

06 - 5. Machine Learning Architectures

01 - Azure Databricks pipeline considerations.mp4

02:49

02 - Azure Databricks for data warehousing.mp4

02:29

03 - Azure Databricks and machine learning.mp4

04:20

04 - Azure Databricks for churn analysis.mp4

02:25

05 - Azure Databricks for intrusion detection.mp4

03:08

07 - Conclusion

01 - Next steps.mp4

01:01

Description

Apache Spark and Microsoft Azure are two of the most in-demand platforms and technology sets in use by today's data science teams. These two platforms join forces in Azure Databricks‚ an Apache Spark-based analytics platform designed to make the work of data analytics easier and more collaborative. In this course, Lynn Langit digs into patterns, tools, and best practices that can help developers and DevOps specialists use Azure Databricks to efficiently build big data solutions on Apache Spark. Lynn covers how to set up clusters and use Azure Databricks notebooks, jobs, and services to implement big data workloads. She also explores data pipelines with Azure Databricks—including how to use ML Pipelines—as well as architectural patterns for machine learning.

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Apache Spark

Microsoft Azure

Lynn Langit

Instructor's Courses

Cloud Architect working with remote dev teams world-wide to build cloud solutions. Author of 30 LinkedIn Learning Cloud/Data courses with over 5 million student views. https://www.linkedin.com/learning/instructors/lynn-langit

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LinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications. It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.