Azure Data Engineer Associate (DP-203) Cert Prep: 2 Design and Develop Data Processing

Focused View

Noah Gift

46:02

137 View

01 - Introduction

01 - Design and develop data processing on Microsoft Azure.mp4

00:30

02 - Quick prerequisite technology overview.mp4

02:20

02 - 1. Ingest and Transform Data

01 - Transform data by using Apache Spark.mp4

05:51

02 - Cleanse data.mp4

05:02

03 - Common data transform tasks.mp4

06:53

03 - 2. Design and Develop a Batch Processing Solution

01 - Develop batch processing solutions.mp4

03:30

02 - Integrate JupyterPython notebooks.mp4

08:28

04 - 3. Design and Develop a Stream Processing Solution

01 - Develop a stream processing solution.mp4

05:33

05 - 4. Manage Batches and Pipelines

01 - Manage batches and pipelines.mp4

04:19

06 - Conclusion

01 - Summary and next steps.mp4

03:36

Description

Are you preparing for the Microsoft Azure Data Engineering (DP-203) exam, or seeking a better understanding of how to design and develop data processing? This course, the second in a series, can help you. Noah Gift, founder of Pragmatic A.I. Labs and a Python Software Foundation Fellow, covers how to design and develop data processing with Azure. Noah shows you how to use Apache Spark, Data Factory, and Databricks to ingest and transform data in Azure. He goes over data cleaning and common data transformation tasks, then dives into batch processing solutions. After explaining how to integrate Jupyter/Python notebooks into your data pipeline, Noah discusses stream processing, the differences between stream and batch processing, and using the Azure Data Factory solution to manage your batches and pipelines.

Note: This course was created by Noah Gift. We are pleased to host this training in our library.

More details

User Reviews

Rating

average 0

Total votes0

Focused display

Data Analysis

Microsoft Azure

Microsoft Certification

Noah Gift

Instructor's Courses

Author of Practical MLOps, Enterprise MLOps, Developing on AWS with C#, Pragmatic AI, and Python for DevOps. Certified on Multiple MLOps certifications including Google-Professional Machine Learning Engineer and AWS Certified Machine Learning - Specialty. Adjunct Professor at Duke MIDS & Northwestern Graduate Data Science & AI. Held business roles including CTO, general manager, consulting CTO, and cloud architect. Consults with start-ups and other companies on machine learning and cloud architecture. AWS ML Hero, Python Software Foundation Fellow, AWS Subject Matter on Machine Learning, AWS Certified Solutions Architect, AWS Certified Machine Learning Specialist, AWS Certified Big Data Specialist, Google Certified Professional Architect, and AWS Academy Accredited Instructor. Published books, videos, and courses on cloud machine learning, DevOps, Python, Data Science, Big Data and AI. ★ Specialties ★ ° Cloud-native Machine Learning and AI ° Directly teaching cutting edge skills to students that lead to jobs ° Creating world-class content in all forms ° Building Companies ° Shipping new Products ° Leading and growing engineering teams ° Production Machine Learning, Deep Learning, Big Data, and AI ° Serverless Data Engineering ° Advising Early Stage Startups/Consulting CTO services ° Distributed Systems and Scalability

Linkedin Learning

View courses Linkedin Learning

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.