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LinkedIn Learning

Master Data Engineering

via LinkedIn Learning Path

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Overview

Data engineering is one of the fastest-growing areas within the tech space. Master the tools and skills needed to be successful in this quickly evolving and in-demand market, such as Kafka, SQL, Python, dbt, and Snowflake.
  • Troubleshoot, debug, and tune Apache Kafka.
  • Build scalable and batch applications.
  • Advance your Python and SQL skills for data engineering.
  • Dive into popular data frameworks like dbt and Snowflake.

Syllabus

Courses under this program:
Course 1: Apache Kafka Essential Training: Building Scalable Applications
-Learn about the scalability and manageability aspects of Apache Kafka and how to build asynchronous applications with Kafka and Java.

Course 2: Troubleshooting and Debugging Kafka
-Learn how to use the Confluent platform to debug and troubleshoot Apache Kafka.

Course 3: Tuning Kafka
-Develop advanced skills to optimize your performance by fine-tuning Apache Kafka.

Course 4: Architecting Big Data Applications: Batch Mode Application Engineering
-Develop the skills required to architect and manage batch processing applications to generate consistent data-driven results.

Course 5: Python for Data Engineering: from Beginner to Advanced
-Practice fundamental skills using Python for data engineering in this hands-on, interactive course with coding challenges in CoderPad.

Course 6: Data Engineering: dbt for SQL
-Learn how you can use dbt (data build tool) to make managing your SQL code simpler and faster.

Course 7: Advanced Snowflake: Deep Dive Cloud Data Warehousing and Analytics
-Supercharge your Snowflake skills with this deep dive into architecture and advanced settings.

Courses

Taught by

Kumaran Ponnambalam, Janani Ravi, Deepak Goyal and Vinoo Ganesh

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