Data Engineering Capstone Project
Apply comprehensive data engineering skills in this hands-on capstone. Build complete data platforms using SQL, NoSQL, Python, ETL, and BI tools.
Apply comprehensive data engineering skills in this hands-on capstone. Build complete data platforms using SQL, NoSQL, Python, ETL, and BI tools.
This intensive capstone project challenges students to design and implement a complete data and analytics platform. Participants will apply advanced data engineering concepts across multiple technologies, including relational and non-relational databases, data warehousing, ETL processes, and BI tools. The project emphasizes hands-on experience with industry-standard tools like Python, SQL, MongoDB, Apache Airflow, and Cognos Analytics. Students will create data pipelines, implement machine learning models, and develop analytical dashboards. This comprehensive project prepares participants for real-world data engineering roles by providing practical experience in building and managing enterprise-level data solutions.
Instructors:
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What you'll learn
Design and implement complete data and analytics platforms
Manage relational and NoSQL databases effectively
Create ETL pipelines using Apache Airflow
Develop BI reports and dashboards with Cognos Analytics
Implement machine learning models using Apache Spark
Build and populate data warehouses using star/snowflake schemas
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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Module Description
This comprehensive capstone project focuses on practical application of data engineering skills. Students will work with multiple databases, implement ETL processes, design data warehouses, and create BI solutions. The course emphasizes hands-on experience with real-world tools and technologies, including Python, SQL, MongoDB, Apache Airflow, and Cognos Analytics. Students will build complete data platforms and implement machine learning models, preparing them for entry-level data engineering positions.
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
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