Introduction to Big Data Analytics: Level-01. Learn to work with Hadoop, Spark, and NoSQL. Perform large-scale data processing and uncover insights using analytics tools.
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Learn to work with Hadoop, Spark, and NoSQL. Perform large-scale data processing and uncover insights using analytics tools.
Enhance skills in processing and managing big data, implement real-time data processing, and build data integration pipelines while performing intermediate data analysis.
Click any module to expand and view topics and hands-on labs included.
Understand the 5 Vs of Big Data, ecosystem components, and career opportunities in the field.
Collect data from APIs, handle batch and streaming ingestion, and understand ETL workflows.
Work with HDFS, MapReduce, Hive, Pig, HBase, and perform large-scale processing with Spark.
Implement streaming pipelines with Kafka and Spark Streaming for real-time insights.
Continue your learning path with these next-step and related courses from Avanteia.
Master enterprise big data with advanced Spark, data lake architecture, and real-time analytics. This Level 2 big data course in Goa covers streaming analytics, data governance, and cloud-based big data solutions. Architect enterprise data platforms.
Develop intermediate data science skills with advanced Python, statistical modeling, and Power BI dashboards. This Level 1 data science course in Goa covers hypothesis testing, regression analysis, and business intelligence reporting. Analyze real-world datasets for insights.
Develop practical Data Analytics skills with Avanteia's 2-month Level 1 program. Learn Excel, SQL, Python, Power BI, Tableau, Statistics & AI Tools while working on practical exercises and real-world data analysis projects.
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I completed the Beginner course first and immediately enrolled in Intermediate. The malware analysis and reverse engineering modules were eye-opening. The 2-month duration is perfect for working professionals.
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Join 8,420+ professionals who have advanced their skills. Enroll today and get certified in just two months.
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