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Big Data Fundamentals with Hadoop and Spark
This course is part of multiple programs. Learn more.
Course Cost
₹ 8,650
Beginner
Skill Level
6 Weeks
Self-paced Video lessons
Discover the power of big data technologies with IBM's foundational course. Learn to process and analyze massive datasets using industry-standard tools like Hadoop and Apache Spark. Explore distributed processing, parallel programming, and data parallelism concepts. Master practical skills in PySpark, Spark SQL, and streaming analytics. Perfect for IT professionals looking to understand big data processing tools and their applications. Gain hands-on experience with real-world scenarios and learn to leverage these technologies for efficient data analysis.
4.5
14,897 Enrolled
English
What you'll learn
Master fundamental concepts of big data and its impact on organizations
Understand Hadoop architecture and ecosystem components including HDFS and MapReduce
Develop skills in Apache Spark programming and parallel processing
Gain practical experience with PySpark and Spark SQL applications
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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There are 7 modules in this course
This course provides a comprehensive introduction to big data technologies and practices. Students learn about the fundamentals of big data processing, including parallel processing, scaling, and data parallelism. The curriculum covers major platforms like Hadoop and Spark, exploring their architectures, components, and applications. Through hands-on labs and practical exercises, participants gain experience with distributed file systems, MapReduce, PySpark, and Spark SQL. The course also covers advanced topics like performance monitoring and tuning, making it valuable for aspiring data engineers and IT professionals.
What is Big Data
Module 1
Introduction to the Hadoop Ecosystem
Module 2
Introduction to Apache Spark
Module 3
DataFrames and SparkSQL
Module 4
Development and Runtime Environment Options
Module 5
Monitoring and Tuning
Module 6
Final Quiz
Module 7
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Data Engineering, NoSQL, Big Data and Spark Fundamentals
Reviews
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Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
4.3
87
Reviews
6,31,843
Students
6
Courses
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.
2
Courses
Karthik Muthuraman serves as a Data Scientist and Developer Advocate at IBM's Center for Open Source Data & AI Technologies (CODAIT), where he focuses on democratizing AI through open-source technologies. After earning his Master's degree in Electrical and Computer Engineering from the University of Michigan, Ann Arbor, with a focus on machine learning and computer vision, he has established himself as an expert in deep learning and AI systems. His work at CODAIT includes developing open-source deep learning models, contributing to frameworks like TensorFlow, and creating innovative applications such as automatic image cropping and age estimation systems
Frequently asked Questions
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