Big Data Engineering Course (3 Modules)

The Big Data Engineering course is comprised of three modules that cover models and practices for designing, configuring and utilizing Big Data solutions, including Big Data storage environments, pipelines and data processing.

Each module has a set of lessons and is further supplemented with exercises and practice questions to help reinforce your understanding of key topics. Completing this course also prepares you for the official certification exam, as explained on the Big Data Engineer Certification page.

Further resources are available to assist you with the completion of this course and preparation for the certification exam. These include downloadable digital course PDFs, printed course materials that can be shipped to your location, as well as coaching and instructor-led training services available by Arcitura and its training partner network. You can purchase coaching time on an hourly basis and instructor-led training workshops are available for individuals and groups.

This course is available via two separate eLearning platforms, each of which has different features and benefits. Upon clicking the Enroll button, you will be able to choose the eLearning option that works best for you.

Contact [email protected] with any questions.

Program: Next-Gen Data Science Academy

Prerequisites: Big Data Analytics & Fundamental Data Science

Duration: 30 hours

Price: from $29

Corresponding Certification:
Big Data Engineer

Inquire About Instructor-Led Training for Your Team

Workbook Lessons

Video Lessons

Reference Posters

Interactive Exercises

Graded Self-Test

Completion Certificate

Course Modules

MODULE 13 | Fundamental Big Data Engineering
Explores on the usage and application of the Hadoop and MapReduce frameworks, as well as a range of Big Data engineering techniques and technologies. Coverage includes Big Data storage models, NoSQL and NewSQL, as well as Big Data processing engines.

MODULE 14 | Advanced Big Data Engineering
Delves into advanced engineering topics pertaining primarily to the storage and processing of Big Data datasets. The module covers advanced Big Data engineering mechanisms, in-memory data storage and realtime data processing, as well as MapReduce algorithms, bulk synchronous parallel processing and graph data processing.

MODULE 15 | Big Data Engineering Lab
Provides a series of exercises and problems designed to test your ability to apply your knowledge of topics covered in previous course modules. Completing this lab will help highlight areas that require further attention and will further help prove proficiency in designing Big Data algorithms processing and data storage environments.