Data Engineering Capstone Project
Apply comprehensive data engineering skills in a real-world project using MySQL, MongoDB, PostgreSQL, and Apache Spark.
Apply comprehensive data engineering skills in a real-world project using MySQL, MongoDB, PostgreSQL, and Apache Spark.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full IBM Data Engineering Professional Certificate program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.7
(105 ratings)
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Instructors:
English
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What you'll learn
Design and implement OLTP and NoSQL databases
Create and manage data warehouses with advanced reporting
Develop ETL pipelines and data transformation workflows
Build analytics dashboards using visualization tools
Perform predictive analytics using Apache Spark
Skills you'll gain
This course includes:
2.5 Hours PreRecorded video
14 quizzes
Access on Mobile, Tablet, Desktop
FullTime 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 7 modules in this course
This comprehensive capstone project simulates real-world data engineering scenarios, requiring students to design and implement a complete data analytics platform. The curriculum covers creating and querying data repositories using MySQL and MongoDB, designing data warehouses with PostgreSQL and IBM Db2, implementing ETL pipelines, and performing big data analytics with Apache Spark. Students also create dashboards using Cognos Analytics and demonstrate their ability to handle various aspects of the data engineering lifecycle.
Data Platform Architecture and OLTP Database
Module 1 · 1 Hours to complete
Querying Data in NoSQL Databases
Module 2 · 1 Hours to complete
Build a Data Warehouse
Module 3 · 4 Hours to complete
Data Analytics
Module 4 · 4 Hours to complete
ETL & Data Pipelines
Module 5 · 2 Hours to complete
Big Data Analytics with Spark
Module 6 · 1 Hours to complete
Final Submission and Peer Review
Module 7 · 2 Hours to complete
Fee Structure
Instructors
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
Data Engineering and Technology Education Expert
Ramesh Sannareddy serves as a freelance technology educator and content developer, bringing over two and a half decades of experience in Information Technology Infrastructure Management, Database Administration, and Information Integration. After earning his Bachelor's Degree in Information Systems from Birla Institute of Technology, Pilani, he built an impressive career working with leading technology companies including Intergraph, Genpact, HCL, and Microsoft. Currently focused on his passion for teaching, he specializes in developing and delivering courses in Data Science, Machine Learning, Programming, and Databases. His educational impact is evidenced through his extensive course portfolio, which includes specialized programs in Data Engineering, Data Warehousing, Linux Commands, Machine Learning with Apache Spark, and Python Programming. His teaching reaches over 11,800 learners globally, maintaining a strong 4.5 rating for his educational content
Testimonials
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4.7 course rating
105 ratings
Frequently asked questions
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