Data Manipulation at Scale: Systems and Algorithms
Master large-scale data analysis using SQL, NoSQL, MapReduce, and distributed systems for effective data science.
Master large-scale data analysis using SQL, NoSQL, MapReduce, and distributed systems for effective data science.
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 Data Science at Scale Specialization 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.
4.3
(766 ratings)
61,276 already enrolled
Instructors:
English
پښتو, বাংলা, اردو, 2 more
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What you'll learn
Master relational algebra and database concepts
Implement MapReduce algorithms for large-scale data processing
Understand NoSQL systems and their trade-offs
Develop scalable data manipulation solutions
Analyze complex graph-structured data
Evaluate different big data systems and architectures
Skills you'll gain
This course includes:
8.4 Hours PreRecorded video
3 programming assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This comprehensive course explores advanced data manipulation techniques and systems for large-scale data analysis. Students learn fundamental concepts in distributed computing, database systems, and algorithmic thinking. The curriculum covers relational algebra, MapReduce programming model, NoSQL systems, and specialized systems for graphs and arrays. Through hands-on programming assignments, learners develop practical skills in implementing scalable data solutions using modern big data platforms and technologies.
Data Science Context and Concepts
Module 1 · 5 Hours to complete
Relational Databases and the Relational Algebra
Module 2 · 5 Hours to complete
MapReduce and Parallel Dataflow Programming
Module 3 · 5 Hours to complete
NoSQL: Systems and Concepts
Module 4 · 2 Hours to complete
Graph Analytics
Module 5 · 1 Hours to complete
Fee Structure
Instructor
Director of Research
Bill Howe is the Director of Research for Scalable Data Analytics at the University of Washington's eScience Institute and holds an Affiliate Assistant Professor position in Computer Science & Engineering. He leads research focused on data management, analytics, and visualization systems tailored for scientific applications. Howe has received multiple awards from Microsoft Research and honors for his contributions to scientific data management.
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4.3 course rating
766 ratings
Frequently asked questions
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