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

Courses under this program:
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 (2019)
-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: 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 8: Cloud NoSQL for SQL Professionals
-Learn how to choose a cloud-based NoSQL database solution that's right for your organization.

Course 9: 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.

Courses

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1 hour 55 minutes
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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.
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1 hour 28 minutes
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Develop the skills required to architect and manage batch processing applications to generate consistent data-driven results.
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1-2 hours
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Learn about use cases and best practices for architecting real-time applications using big data technologies, such as Hazelcast and Apache Spark.
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2 hours 40 minutes
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Learn how to choose a cloud-based NoSQL database solution that's right for your organization.
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53 minutes
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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.
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1-2 hours
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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.
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Get a high-level view of the basics of NoSQL, from how it differs from relational databases to its pros and cons.
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2-3 hours
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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.
0 reviews

View details

Get Ben Sullins's 12 must-have SQL techniques for data science pros—engineers, DevOps, data miners, programmers, and other systems specialists.