Data Engineering Fundamentals
Master the essentials of data engineering, from data pipelines to warehousing, and learn how to effectively manage and process data for business insights.
Master the essentials of data engineering, from data pipelines to warehousing, and learn how to effectively manage and process data for business insights.
This comprehensive course introduces the fundamentals of data engineering, covering the complete ecosystem and lifecycle. Students learn about data platforms, repositories, integration tools, and pipelines essential for modern data management. The curriculum explores various data storage solutions including relational and non-relational databases, data warehouses, and data lakes. Through hands-on labs using IBM Cloud, participants gain practical experience in data store provisioning, data preparation, and basic operations. The course also covers big data concepts, career opportunities in data engineering, and industry best practices, making it ideal for those looking to enter or advance in the field.
4.7
(26 ratings)
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Instructors:
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What you'll learn
Understand core data engineering concepts and responsibilities
Master the complete data engineering lifecycle and key processes
Explore different layers of data platform architecture
Learn about various data storage solutions and integration tools
Gain practical experience with IBM Cloud data services
Understand career paths and opportunities in data engineering
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
Shareable certificate
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Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 4 modules in this course
This introductory course provides a comprehensive overview of data engineering concepts and practices. The curriculum is structured around understanding the data engineering ecosystem, lifecycle, and career opportunities. Students learn about various components of data platforms, including data repositories, integration tools, and business intelligence solutions. The course emphasizes practical applications through hands-on labs using IBM Cloud, teaching students how to manage and process data effectively. Special attention is given to big data concepts and their impact on modern data engineering practices.
What is Data Engineering
Module 1
Data Engineering Ecosystem
Module 2
Data Engineering Lifecycle
Module 3
Career Opportunities and Learning Paths
Module 4
Fee Structure
Instructor
Technology Education and Skills Development Leader at IBM
Rav Ahuja serves as the Chief Content Officer and Global Program Director at IBM Skills Network, where he leads curriculum creation, growth strategy, and partner programs. After earning his B.Eng. from McGill University and MBA from the University of Western Ontario, he co-founded Cognitive Class, an IBM initiative focused on democratizing access to in-demand technology skills. Based at the IBM Canada Lab in Toronto, he specializes in developing instructional solutions for AI, Data Science, Cloud Computing, and Cybersecurity. His impact on technology education is evidenced through his role as architect of numerous IBM Professional Certificates and instructor for over 35 online courses, including popular offerings like "What is Data Science?", "Introduction to Cloud Computing," and "Introduction to Artificial Intelligence (AI)." His courses have reached hundreds of thousands of learners worldwide, with "What is Data Science?" alone enrolling over 638,000 students. His recent work includes developing new Generative AI courses and career guidance content for IBM's Professional Certificate programs, demonstrating his ongoing commitment to preparing learners for emerging technology careers
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4.7 course rating
26 ratings
Frequently asked questions
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