Master essential Big Data technologies and tools in this beginner's course. Learn processing, analysis, and real-world applications.
Master essential Big Data technologies and tools in this beginner's course. Learn processing, analysis, and real-world applications.
This comprehensive course introduces the fundamentals of Big Data technologies and their practical applications. Students learn essential concepts, tools, and techniques for processing and analyzing massive datasets. The curriculum covers the Hadoop ecosystem, Apache Spark, real-time processing with Kafka, and machine learning applications. Tailored for data professionals and analysts, the course explores real-world applications across e-commerce, healthcare, and finance sectors.
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Instructors:
English
What you'll learn
Explain the characteristics and challenges of Big Data
Identify different Big Data technologies and their roles
Apply Big Data tools to derive insights from large datasets
Explore real-world applications across various domains
Skills you'll gain
This course includes:
51 Minutes PreRecorded video
1 assignment,2 discussion prompts
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FullTime access
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There is 1 module in this course
This introductory course covers essential concepts and applications of Big Data technologies. The curriculum explores the characteristics and challenges of Big Data, introducing various technologies and their roles in data processing and analysis. Through comprehensive modules, students learn about the Hadoop ecosystem, Apache Spark, machine learning with Big Data, and real-time processing with Apache Kafka. The course includes practical applications across e-commerce, healthcare, and finance sectors.
Big Data Technologies and Applications
Module 1 · 1 Hours to complete
Fee Structure
Payment options
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Instructor
Data Science Expert and Business Intelligence Innovator
Caio Avelino brings extensive expertise in Data Science, Business Intelligence, and Artificial Intelligence, combining academic excellence with practical industry experience. His educational background includes a degree in Electrical Engineering from Unicamp, international experience at Monash University in Melbourne, and specialized training in Data Science from Data Science Academy. As an instructor and professional, he specializes in complex analytics, dashboard development, and Machine Learning model creation. His teaching portfolio includes courses in Big Data Technologies, Data Warehousing, Business Intelligence, and Advanced Statistical Analysis using Seaborn. His approach emphasizes practical problem-solving and continuous learning, particularly in startup environments where he has contributed to developing innovative data solutions. His passion for knowledge sharing is evident through his training programs, helping colleagues and students master data science concepts. Currently pursuing further studies in Artificial Intelligence, he maintains a commitment to staying at the forefront of technological advancement while making complex technical concepts accessible to learners.
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Frequently asked questions
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