Edureka
Data Streaming and NLP with PySpark
Edureka

Data Streaming and NLP with PySpark

Edureka

Instructor: Edureka

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

Recommended experience

15 hours to complete
3 weeks at 5 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

15 hours to complete
3 weeks at 5 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Analyze streaming data to extract insights and trends in real-time applications.

  • Analyze real-time data streams and apply Spark Streaming techniques for efficient processing.

  • Develop robust streaming applications using Spark's Structured Streaming for fault-tolerant processing.

  • Implement NLP techniques to process and analyze textual data efficiently.

Details to know

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Recently updated!

October 2024

Assessments

16 assignments

Taught in English

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Build your subject-matter expertise

This course is part of the PySpark for Data Science 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
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There are 5 modules in this course

This module introduces the fundamentals of stream processing with Apache Spark. It covers how data is processed in real-time, the various models for handling data streams, and different architectures used in stream processing systems.

What's included

16 videos4 readings4 assignments1 discussion prompt

In this module, learners will explore Spark Streaming, its core concepts, and the evolution towards Structured Streaming. They will gain an understanding of the DStream abstraction, and the structure of Spark Streaming applications, and explore transformations alongside recent updates.

What's included

8 videos4 readings3 assignments1 discussion prompt

In this module, learners are introduced to the fundamental concepts of Structured Streaming in Spark, with a focus on its programming model, core operations, and management of streaming workflows. They will explore structured data processing in both batch and stream contexts.

What's included

33 videos4 readings4 assignments1 discussion prompt

This module covers the integration of PySpark with Deep Learning and Natural Language Processing (NLP), followed by optimization strategies for PySpark applications. Learners will explore the foundations of deep learning, NLP techniques, and best practices for performance tuning.

What's included

29 videos5 readings4 assignments2 discussion prompts

This module is meant to test how well you understand the different ideas and lessons you've learned in this course. You will undertake a project based on Spark NLP and complete a comprehensive quiz that will assess your confidence and proficiency in Data Streaming and NLP with PySpark.

What's included

1 video1 reading1 assignment1 discussion prompt

Instructor

Edureka
Edureka
44 Courses39,083 learners

Offered by

Edureka

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