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Become a Data Engineer: Mastering the Concepts

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Free Online Course: Become a Data Engineer: Mastering the Concepts provided by LinkedIn Learning is a comprehensive online course, which lasts for 13 hours worth of material. The course is taught in English and is free of charge. Upon completion of the course, you can receive an e-certificate from LinkedIn Learning. Become a Data Engineer: Mastering the Concepts is taught by Ben Sullins, Mel McGee, Kumaran Ponnambalam, Kumaran Ponnambalam, Kumaran Ponnambalam, Emma Saunders, Dan Sullivan, Ben Sullins and Lynn Langit.

via LinkedIn Learning
13 hours worth of material
Self Paced
Overview

  • Build extensive data engineering and DevOps skills as you learn essential concepts. With this learning path, master the tools of the trade and how to apply them in real-world data project environments and platforms.

    • Build a foundation in data engineering and data science DevOps.
    • Explore techniques deployed in common tools and platforms.
    • Develop deeper skills in data science application programming.

Syllabus

    • Course 1: Data Science Foundations: Data Engineering
      • Discover the basics of big data with a data science expert. Learn about how to perform core data engineering tasks including staging, profiling, cleansing, and migrating data.
    • Course 2: NoSQL Essential Training
      • Get a high-level view of the basics of NoSQL, from how it differs from relational databases to its pros and cons.
    • Course 3: Apache Spark Essential Training: Big Data Engineering
      • Learn how to make Apache Spark work with other Big Data technologies and put together an end-to-end project that can solve a real-world business problem.
    • Course 4: Architecting Big Data Applications: Batch Mode Application Engineering
      • Learn about use cases and best practices for architecting batch mode applications using big data technologies such as Hive and Apache Spark.
    • Course 5: Architecting Big Data Applications: Real-Time Application Engineering
      • Learn about use cases and best practices for architecting real-time applications using big data technologies, such as Hazelcast and Apache Spark.
    • Course 6: SQL: Data Reporting and Analysis
      • Get the data you need for analysis and reporting by writing your own SQL code. Learn how to write basic SQL queries, sort and filter data, and join results from different tables.
    • Course 7: Advanced NoSQL for Data Science
      • Explore the fundamentals of NoSQL. Learn the differences between NoSQL and traditional relational databases, discover how to perform common data science tasks with NoSQL, and more.
    • Course 8: SQL Tips and Tricks for Data Science
      • Get Ben Sullins's 12 must-have SQL techniques for data science pros—engineers, DevOps, data miners, programmers, and other systems specialists.
    • Course 9: Cloud NoSQL for SQL Professionals
      • Learn how to choose a cloud-based NoSQL database solution that's right for your organization.

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