Introduction to Big Data with Spark and Hadoop
Master Big Data processing with Apache Hadoop & Spark! Learn to use these tools and their ecosystems for efficient data management & analytics.
Master Big Data processing with Apache Hadoop & Spark! Learn to use these tools and their ecosystems for efficient data management & analytics.
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.
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What you'll learn
Implement big data solutions using Hadoop ecosystem
Develop applications with Apache Spark and RDDs
Optimize queries using Spark SQL and DataFrames
Manage and monitor Spark applications
Master distributed computing concepts
Skills you'll gain
This course includes:
2.7 Hours PreRecorded video
14 assignments
Access on Mobile, Desktop, Tablet
FullTime access
Shareable certificate
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There are 7 modules in this course
This comprehensive course explores big data processing using Apache Hadoop and Spark frameworks. Students learn about distributed computing principles, parallel processing, and data parallelism. The curriculum covers the Hadoop ecosystem including HDFS, MapReduce, Hive, and HBase, along with Spark's capabilities in data processing and analysis. Through hands-on labs using Docker and Kubernetes, participants gain practical experience with DataFrame operations, SparkSQL, and cluster management.
What Is Big Data?
Module 1 · 1 Hours to complete
Introduction to the Hadoop Ecosystem
Module 2 · 2 Hours to complete
Apache Spark
Module 3 · 2 Hours to complete
DataFrames and Spark SQL
Module 4 · 2 Hours to complete
Development and Runtime Environment Options
Module 5 · 3 Hours to complete
Monitoring and Tuning
Module 6 · 2 Hours to complete
Final Project and Assessment
Module 7 · 4 Hours to complete
Fee Structure
Instructors
Data Scientist Aije Egwaikhide: Empowering Women in STEM and Innovating AI Solutions at IBM
Aije Egwaikhide is a fantastic example of how dedication and passion can lead to a successful career in tech! With her background in Economics and Statistics, paired with advanced qualifications in Business and Management Analytics, she’s truly paving the way in the field of data science. Her work at IBM, particularly in creating innovative machine learning solutions for the Oil and Gas sector, is an inspiring achievement.
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
Testimonials
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4.4 course rating
358 ratings
Frequently asked questions
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