Big Data Developer
Data and Big DataThis course is tailored for developers and data engineers who want to specialize in building systems that process and analyze massive volumes of data.
Overview
Course Description
This course is tailored for developers and data engineers who want to specialize in building systems that process and analyze massive volumes of data. You’ll learn how to work with distributed computing tools and modern data processing frameworks used in real-world big data environments.
From data ingestion and storage to processing and visualization, the course covers the entire big data pipeline with hands-on experience and practical use cases.
📚 What You’ll Learn:
Core concepts of Big Data architecture
Working with Hadoop, Spark, and Kafka
Batch vs. real-time data processing
Data storage using HDFS, Hive, and NoSQL databases (e.g., Cassandra, HBase)
Data ingestion tools like Apache Flume, NiFi, or Kafka Connect
Writing and optimizing Spark jobs with PySpark or Scala
🛠️ Skills You’ll Gain:
Building scalable and fault-tolerant data pipelines
Transforming raw data into structured insights
Managing distributed data processing systems
Monitoring, debugging, and optimizing big data workflows
Course Content
Note
Core Concepts of Big Data Architecture
-
Section 1
-
Core Concepts of Big Data Architecture
20.00%
Working with Hadoop, Spark, and Kafka
-
Section 2
-
Working with Hadoop, Spark, and Kafka
20.00%
Batch vs. Real-Time Data Processing
-
Section 3
-
Batch vs. Real-Time Data Processing
20.00%
Data storage using HDFS, Hive, and NoSQL databases (e.g., Cassandra, HBase)
-
Section 4
-
Data storage using HDFS, Hive, and NoSQL databases (e.g., Cassandra, HBase)
20.00%
Data ingestion tools like Apache Flume, NiFi, or Kafka Connect
-
Section 6
-
Data ingestion tools like Apache Flume, NiFi, or Kafka Connect
20.00%
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