Data Engineering: Pipelines, ETL, Hadoop
Learn to build robust data pipelines, implement ETL processes, and master Hadoop ecosystem for large-scale data processing.
Learn to build robust data pipelines, implement ETL processes, and master Hadoop ecosystem for large-scale data processing.
This comprehensive course teaches data engineering fundamentals, focusing on building scalable data pipelines and ETL processes. Students learn to extract data from various sources, transform it effectively, and load it into data warehouses using industry-standard tools. The curriculum covers the Hadoop ecosystem, including HDFS, MapReduce, Hive, Pig, and Spark, preparing learners to handle big data challenges in real-world scenarios.
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What you'll learn
Analyse the architecture and components of data pipelines
Implement robust ETL processes for scalability
Analyze big data challenges using Hadoop ecosystem tools
Design and execute data processing solutions
Skills you'll gain
This course includes:
70 Minutes PreRecorded video
1 assignment,2 discussion prompts
Access on Mobile, Tablet, Desktop
FullTime access
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There is 1 module in this course
This comprehensive data engineering course focuses on building robust data pipelines, implementing ETL processes, and mastering the Hadoop ecosystem. Students learn to analyze pipeline architecture, implement scalable ETL processes, and handle big data challenges. The curriculum covers essential Hadoop tools including HDFS, MapReduce, Hive, Pig, and Spark, providing hands-on experience in extracting, transforming, and loading data from various sources into data warehouses or big data platforms.
Lesson 1: Boosting Customer Success with GenAI
Module 1 · 24 Minutes to complete
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Instructor
Global Finance and Technology Expert Arkadi Avanesyan Bridges Investment Banking with Digital Innovation
Arkadi Avanesyan has established himself as a distinguished expert bridging finance, technology, and data science through his comprehensive academic background, including a BSc in Engineering and MSc in Quantitative Finance from the Free University of Brussels. His impressive eight-year investment banking career resulted in the development of investable indices managing over €1.3bn AUM through structured products with major institutions like Société Générale, Goldman Sachs, and Deutsche Bank. Since 2019, his consulting practice has expanded to serve Fortune 500 companies, investment funds, and SMEs across the United States, Europe, and Dubai, while his role as a mentor on codementor.io has impacted over 850 clients in data science and programming. His technical expertise is further demonstrated through his work with Aigora, where he developed cloud infrastructure for more than 20 projects, and his contribution to the World Bank as an external consultant training global teams. Currently, he focuses on corporate training and creating high-quality courses while maintaining his private client practice.
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