Packt

Advanced Data Engineering with AI and Stream Processing

Packt

Advanced Data Engineering with AI and Stream Processing

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Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

9 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

9 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Design and implement batch and streaming data pipelines

  • Process and analyze large datasets using Apache Spark

  • Build and manage AWS data lakes with S3, EMR, and Athena

Details to know

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Recently updated!

October 2026

Assessments

5 assignments

Taught in English

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This course is part of the The Data Engineering Bootcamp- Zero to Mastery Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 4 modules in this course

This module provides a comprehensive overview of building and evaluating machine learning models using Spark ML. Learners will explore regression and classification techniques, pipeline creation, and model optimization strategies. By the end, they will have practical skills to develop and refine machine learning solutions.

What's included

23 videos1 reading1 assignment

This module introduces learners to the integration of AI in data engineering, focusing on pre-LLM NLP techniques, transformer models, and practical applications using Hugging Face and Databricks. It covers the fundamentals of LLMs, structured output generation, and their implementation with Apache Spark, providing a hands-on approach to real-world data workflows.

What's included

11 videos1 assignment

This module provides an in-depth exploration of real-time data processing using Apache Kafka, covering fundamental concepts, architecture, and practical applications. Learners will gain hands-on experience with setting up Kafka, writing to and reading from Kafka, and understanding advanced features like transactions and schema management. By the end, learners will be equipped to design and implement stream processing solutions.

What's included

24 videos1 assignment

This module provides an in-depth exploration of stream processing using Apache Flink, covering its core concepts, application development, and advanced features like windowing and state management. Learners will gain hands-on experience with setting up Flink and implementing stream processing techniques. The module emphasizes practical skills for real-time data analysis and anomaly detection.

What's included

19 videos1 reading2 assignments

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Instructor

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Packt
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