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Streaming Data Pipelines Virtual Internship

In this advanced virtual internship, students will learn to build real-time data processing pipelines using stream processing technologies like Apache Kafka, Apache Spark Streaming, and Amazon Kinesis. They will gain hands-on experience in designing, implementing, and deploying scalable and fault-tolerant data pipelines that can handle high-velocity, high-volume data streams. The program will cover topics such as stream processing concepts, event-driven architecture, data ingestion, transformation, and analytics, equipping students with the skills to thrive in the fast-paced world of big data and real-time analytics.

weeks
8 tasks
0 enrolled
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Track price: $49.00

Track Overview

This track provides hands-on experience and real-world projects to build your skills.

Tasks & Milestones

Comparing Batch and Stream Processing

Advanced

Analyze the differences between batch and stream processing, and identify use cases where each approach is more suitable.

8 hours

Exploring Stream Processing Architectures

Advanced

Investigate the key components and architectural patterns of stream processing systems.

10 hours

Implementing a Kafka Producer and Consumer

Advanced

Build a simple application that produces and consumes data using the Apache Kafka API.

15 hours

Deploying a Kafka Cluster

Advanced

Configure and deploy a Kafka cluster for a production environment.

20 hours

Building a Spark Streaming Application

Advanced

Develop a Spark Streaming application that processes real-time data from a Kafka topic.

25 hours

Optimizing Spark Streaming Performance

Advanced

Analyze and optimize the performance of a Spark Streaming application.

20 hours

Implementing a Kinesis Data Pipeline

Advanced

Build a real-time data processing pipeline using Amazon Kinesis Data Streams and Kinesis Data Firehose.

25 hours

Integrating Kinesis with Other AWS Services

Advanced

Extend the Kinesis-based data pipeline by integrating it with other AWS services for end-to-end data processing.

20 hours

Prerequisites

  • • Proficiency in a programming language (Python, Java, or Scala)
  • • Experience with databases and data modeling
  • • Understanding of distributed systems and cloud computing concepts

Certificate

Certificate of Completion

Earn a certificate upon successful completion